Joanna Moody, Ph.D.

Research Program Manager, Mobility Systems Center

MIT Energy Initiative

Use of Exclusive and Pooled Ridehailing Services

Ongoing Research

How does the introduction of pooled service influence the behavior of riders (and drivers)? Case studies in 3 Mexican Cities

This study leverages Didi's launch of its comparte or pooled service in three cities in Mexico as a natural experiment to study how the availability of new service offerings influences the trip behavior of users and drivers and how these responses differ across markets. Using data from before and after the launch of Didi's pooled service in Merida (launched in Feburary 2019), Toluca (launched in September 2019), and Aguascalientes (launched in December 2019), we look at how current users and drivers continue to use the express or exclusive service versus adopt the new pooled service, and how new service offerings might expand the user and driver base.

Working Papers

Moody, J., E. Esparza-Villarreal, and D. Keith. "Use of exclusive and pooled ridehailing services in three Mexican cities"


Kong, H., J. Moody, and J. Zhao. (2020). ICT's impact on ride-hailing use and individual travel. Transportation Research Part A: Policy and Practice, 141: 1-15.

Previous studies have explored the relationships between an individual's use of information and communication technology (ICT) and their travel. However, these studies often focus on one speci c type of travel and have not considered new forms of mobility, such as ride-hailing, that are enabled by greater ICT penetration. This paper focuses on how ICT use impacts an individual’s self-reported travel behavior—including total number of trips, personal miles traveled (PMT), and vehicle miles traveled (VMT) in a typical travel day—and ride-hailing use in the past month. Specifically, we investigate whether substitution or complementarity dominates the relationships between ICT use and an individual's net travel; how ICT impacts individual ride-hailing adoption and frequency of use; and how ride-hailing use is associated with an individual's overall travel behavior. Using data from the 2017 U.S. National Household Travel Survey (NHTS), we estimate a structural equation model that includes a robust set of individual, household, built environment, and travel characteristics, frequency of ICT use, and a hurdle model (two-part regression) of the adoption and frequency of ride-hailing use. Results reveal that greater ICT is not significantly related to the total number of trips that an individual takes, but it does significantly predict higher PMT and VMT. Greater ICT use is positively and substantively correlated with whether or not the individual has used ride-hailing in the past 30 days, but has no significant relationship with the frequency of ride-hailing use with this bounded outcome being controlled for. We further find that an individual's ride-hailing use has a small negative correlation with their PMT and VMT after controlling for other common factors. Our results indicate the importance of future research examining the mechanisms by which ICT use increases the distance individuals travel and the role that new ICT-enabled modes, such as ride-hailing, play in changing these mechanisms at both the individual and system levels.

Moody, J., and J. Zhao. (2020) Adoption of exclusive and pooled TNC services in Singapore and the U.S. ASCE's Journal of Transportation Engineering, Part A: Systems, 146(9): 04020102.

On-demand mobility services provided by transport network companies (TNCs) have experienced significant growth in their adoption and diversification of services in major metropolitan cities around the world. This study presents analysis of primary data from Singapore, exploring the sociodemographics of TNC users, who (among these TNC users) is more likely to pool their trips, and what modes these services are replacing. We compare these results to a comprehensive literature review of similar studies of TNC users in the metropolitan U.S. We find that the sociodemographics of TNC users in general are similar in Singapore and the U.S.: younger, highly educated, and higher income individuals are more likely to have used TNC services. On the other hand when differentiating by type of TNC service, we find that younger individuals from households that do not own a car are more likely to have pooled in Singapore, while employment is an important predictor in the U.S. We also find differences in mode substitution; while TNC trips in the U.S. primarily induce additional trips or replace trips by public and non-motorized transport, in Singapore they primarily replace personal/private vehicle trips. In Singapore, we explore mode substitution by exclusive and pooled TNC services separately, finding that pooled trips draw more from public and non-motorized transport, while exclusive trips replace more personal/private vehicle trips. These results suggest that people in Singapore view exclusive and pooled TNC services as distinct travel options that may be more closely related to other private or public transport, respectively. Differences between Singapore and the U.S. highlight the importance of accounting for local context and suggests that the quality of all travel alternatives in the urban area will affect the mode substitution of TNC trips.

Moody, J., S. Middleton, and J. Zhao. (2019). Rider-to-rider discriminatory attitudes and ridesharing behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 62: 258-273.

Using online survey data from N = 2,041 Uber and Lyft users in the United States collected in 2016 and 2018, this paper establishes the validity, reliability, and invariance of a measure of rider-to-rider race and social class discrimination. This measure is then incorporated into three structural models that investigate associations between rider-to-rider discriminatory attitudes and four aspects of ridesharing behavior. We find that rider-to-rider discriminatory attitudes do not significantly predict whether a TNC user has used a ridesharing service (such as uberPOOL or Lyft Line). However, among those who have used ridesharing services before, rider-to-rider discriminatory attitudes are strongly negatively predictive of an individual's level of satisfaction with the sharing option, and marginally negatively predictive of an individual's percentage of shared TNC trips. Furthermore, among those who have not yet used ridesharing services, rider-to-rider discriminatory attitudes are strongly negatively predictive of willingness to consider using uberPOOL or Lyft Line in the future. These associations between rider-to-rider discriminatory attitudes and multiple aspects of ridesharing behavior suggest that such attitudes may persistently discourage sharing. In fact, we find no statistically significant difference in rider-to-rider discrimination or in its relations with ridesharing behavior across the two survey years. Further research is required to identify strategies for addressing discriminatory attitudes in the ridesharing context and overcoming reluctance to sharing.

Image source: Nucleo Editorial/Flikr (CC BY 2.0)