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：拼车出行——一种乘客与其他乘客共享车辆的网约车服务——已成为部分主要城市的常见出行方式。目前，优步、来福车和Via等交通网络公司均提供此类共享出行选项，并吸引了越来越多的用户，尤其在新冠疫情前。以往研究指出，拼车出行可通过减少运送人员所需的车辆数量来降低出行成本，甚至缓解交通拥堵。近期研究还推测，拼车出行应具有正反馈机制，即服务质量会随用户数量提高而改善。具体而言，这类系统应受益于规模经济和规模报酬递增。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出行数据，验证了这些效应的存在。研究表明，在特定时间段内，请求或授权拼车出行的乘客数量增加，与以下现象相关：更短的行程绕行距离、更高的乘客匹配率、相较于非共享出行的更低成本，以及乘客更高的共享出行意愿。