Does Adoption of Ridehailing Result in More Frequent Sustainable Mobility Choices? An Investigation Based on the National Household Travel Survey (NHTS) 2017 Data

Abstract

Among many changes potentially induced by the adoption of ridehailing, one key area of interest in transportation and urban planning research is how these services affect sustainable mobility choices, such as usage of public transit, walking, and biking modes and lower ownership of household vehicles. In this study, by using subsamples of the National Household Travel Survey (NHTS) 2017 data, propensity score matching technique is applied to generate matched samples of ridehailing adopters and non-adopters from ten different core-based statistical areas in the U.S. Results from multivariable count data regression models built on the matched samples indicate that, on average, the count of public transit trips is greater for adopters compared against identical non-adopters in all ten areas. Regarding average counts of walking and biking trips, adopters tend to make more trips in most of the places, although a few exceptions are also found. However, the relationship between ridehailing adoption and count of household vehicles appears to be more complicated as adopters, on average, seem to have a lower or higher number of vehicles than identical non-adopters, depending on the area. One major limitation of this study is that, in the statistical analyses, effects of attitudinal and detailed geographic variables are not directly controlled for, which complicates causal interpretations of findings.

Spatial equity implications and neighborhood indicators of ridehailing trip frequency and vehicle miles traveled in the phoenix metro region

“…Regarding travel patterns, a positive association has been consistently found between ridehailing adoption and higher VMT totals than would be observed without its availability (Henao and Marshall 2019;Tirachini and Gomez-Lobo 2019;Das 2020). An outcome likely attributed to deadheading, which is defined as the miles that a ridehailing driver travels without a passenger inside their vehicle (Nair et al 2020).…”

“…In an early survey-based study, Rayle et al (2016) found that 60% of ridehailing passengers in San Francisco were male and 75% of respondents were younger than 35 years. Ridehailing passengers also seem more likely to adopt non-car travel modes including public transit (Conway et al 2018;Grahn et al 2019;Sikder 2019;Das 2020), with technological aptitude also identified as an indicator of ridehailing adoption (Lavieri and Bhat 2019).…”

Nonlinear Relationships between Vehicle Ownership and Household Travel Characteristics and Built Environment Attributes in the US Using the XGBT Algorithm

“…It encompasses non-commercial travel on a daily basis in all commute modes and the features of the travellers, their households, and their vehicles. Several researchers employed these data for different purposes, including investigation of trends in taxi use and ride hailing [41][42][43], determining the occurrence of rural and urban cycling [44,45], ownership and usage assessment of unconventional fuel vehicles [46], preferences of public transportation users [47], and so on. A summary of some studies that used 2017 NHTS data is shown in Table 1.…”

Mobility-as-a-Service: Simulation of Multi-Modal Operations in Low-Density Cities

“…Knowledge on the behavioral side is also inconsistent. While surveys have shown that ridesourcing adopters are more likely to participate in more sustainable mobility choices, a different study finds that using ridesourcing services results in a 6% drop in transit use among adopters in major American cities (33,34). Further, the effects of poor multi-modal integration have been proven to significantly affect emissions because of increased conflicts with cyclists and pedestrians (35).…”