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Title: A behavioral choice model of the use of car-sharing and ride-sourcing services

Abstract

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
U.S. Department of Transportation (DOT)
OSTI Identifier:
1415129
Report Number(s):
NREL/JA-5400-70724
Journal ID: ISSN 0049-4488
DOE Contract Number:
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: Transportation; Journal Volume: 44; Journal Issue: 6
Country of Publication:
United States
Language:
English
Subject:
30 DIRECT ENERGY CONVERSION; ride-sourcing services; car-sharing services; bivariate ordered probit model; market adoption and use of disruptive mobility services; travel demand forecasting

Citation Formats

Dias, Felipe F., Lavieri, Patrícia S., Garikapati, Venu M., Astroza, Sebastian, Pendyala, Ram M., and Bhat, Chandra R. A behavioral choice model of the use of car-sharing and ride-sourcing services. United States: N. p., 2017. Web. doi:10.1007/s11116-017-9797-8.
Dias, Felipe F., Lavieri, Patrícia S., Garikapati, Venu M., Astroza, Sebastian, Pendyala, Ram M., & Bhat, Chandra R. A behavioral choice model of the use of car-sharing and ride-sourcing services. United States. doi:10.1007/s11116-017-9797-8.
Dias, Felipe F., Lavieri, Patrícia S., Garikapati, Venu M., Astroza, Sebastian, Pendyala, Ram M., and Bhat, Chandra R. Wed . "A behavioral choice model of the use of car-sharing and ride-sourcing services". United States. doi:10.1007/s11116-017-9797-8.
@article{osti_1415129,
title = {A behavioral choice model of the use of car-sharing and ride-sourcing services},
author = {Dias, Felipe F. and Lavieri, Patrícia S. and Garikapati, Venu M. and Astroza, Sebastian and Pendyala, Ram M. and Bhat, Chandra R.},
abstractNote = {There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.},
doi = {10.1007/s11116-017-9797-8},
journal = {Transportation},
number = 6,
volume = 44,
place = {United States},
year = {Wed Jul 26 00:00:00 EDT 2017},
month = {Wed Jul 26 00:00:00 EDT 2017}
}