Suggested Citation:
Circella, Giovanni, Yongsung Lee, Ilsu Kim, Patricia L. Mokhtarian, Grace Chen (2024)

 If Pooling with a Discount were Available for the Last Solo-Ridehailing Trip, How Much Additional Travel Time Would Users Have Accepted and for Which Types of Trips?

. Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-24-03

Abstract:

Pooled trips in private vehicles, or pooling, can lead to smaller environmental impacts and more efficient use of the limited roadway capacity, especially during peak hours. However, pooling has not been well adopted in part because of difficulties in coordinating schedules among various travelers and the lack of flexibility to changes in schedules and locations. In the meantime, ridehailing (RH) provides pooled services at a discounted fare (compared to the single-travel-party option) via advanced information and communication technology. This study examines individuals’ preferences for/against pooled RH services using information collected among travelers answering a set of questions related to their last RH trip. In doing so, both trip attributes and rider characteristics are considered. Taste heterogeneity is modeled in a way that assumes the presence of unobserved groups (i.e., latent classes), each with unique preferences, in a given sample of RH riders (N=1,190) recruited in four metropolitan regions in Southern U.S. cities from June 2019 to March 2020. The researchers find two latent classes with qualitatively different preferences, choosy poolers and non-selective poolers, regarding their choice in favor of/against pooling based on wait time, travel costs, purpose, and travel party size of the last RH trip. Personal characteristics are also identified, specifically age and three attitudes (travel satisfaction, environmentalism, and travel multitasking), which account for individuals’ class membership. This research contributes to the literature by explicitly modeling taste heterogeneity towards pooled ridehailing. In addition, unlike existing studies either at the person level or employing stated-preference data, a trip-level analysis is performed in connection with revealed preferences, which generates more realistic and relevant implications to policy and practice.