Ridesplitting -- a type of ride-hailing in which riders share vehicles with other riders -- has become a common travel mode in some major cities. This type of shared ride option is currently provided by transportation network companies (TNCs) such as Uber, Lyft, and Via and has attracted increasing numbers of users, particularly before the COVID-19 pandemic. Previous findings have suggested ridesplitting can lower travel costs and even lessen congestion by reducing the number of vehicles needed to move people. Recent studies have also posited that ridesplitting should experience positive feedback mechanisms in which the quality of the service would improve with the number of users. Specifically, these systems should benefit from economies of scale and increasing returns to scale. This paper demonstrates evidence of their existence using trip data reported by TNCs to the City of Chicago between January and September 2019. Specifically, it shows that increases in the number of riders requesting or authorizing shared trips during a given time period is associated with shorter trip detours, higher rates of riders being matched together, lower costs relative to non-shared trips, and higher willingness for riders to share trips.

翻译：拼车——一种乘客与其他乘客共享车辆的网约车出行方式——已成为部分大城市常见的出行模式。目前，优步（Uber）、来福车（Lyft）和Via等交通网络公司（TNCs）提供此类共享出行服务，吸引了越来越多的用户，尤其在新冠疫情之前。既往研究表明，拼车可降低出行成本，甚至通过减少运载乘客所需车辆数量来缓解交通拥堵。近年来研究也指出，拼车应存在正反馈机制——服务质量会随用户数量提升而改善。具体而言，这类系统应受益于规模经济与规模报酬递增。本文利用2019年1月至9月交通网络公司向芝加哥市报告的行程数据，验证了上述效应的存在。研究显示，在给定时间段内，请求或授权共享行程的乘客数量增加，与以下指标显著相关：行程绕行距离缩短、乘客匹配成功率提升、拼车相较于非共享行程的成本优势扩大，以及乘客拼车意愿增强。