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Title:

User Identification of and Attitude Toward Dynamic Ridesourcing Services

Accession Number:

01626070

Record Type:

Component

Abstract:

Media coverage of ridesourcing services such as Uber and Lyft has described a rivalry between new technology and the established taxi industry. Individual users and non-users of ridesourcing may have more nuanced perspectives, but policymakers have had little guidance on how to best represent these interests. This study uses a standardized questionnaire distributed across the United States by an online survey company to understand individual attitudes toward Uber, Lyft, and ridesourcing technology in general. The survey asks respondents if they identify as users or non-users of ridesourcing, why or why not, how they rank Uber and Lyft among their other travel modes, and their attitudes toward the companies and toward the technology in general, among other questions. The survey returned 394 completed questionnaires from the most populous 15 metropolitan statistical areas in the U.S. with a response rate of 27%. Analysis of the results includes descriptive statistics, bivariate correlation analyses of relationships between variables, and logistic regressions to identify factors that impact user identification and attitude. The findings indicate that about 70% of respondents use some form of ridesourcing, mostly for special-purpose trips such as avoiding driving while intoxicated and getting to and from the airport. There are relationships between transportation needs and user identification and attitude, but demographics are the best predictor of user identification, which in turn predicts attitude, which can predict individuals’ policy preferences. The study suggests potential for policymakers to leverage constituent perspectives to change aspects of ridesourcing that have low public approval.

Supplemental Notes:

This paper was sponsored by TRB committee AP020 Standing Committee on Emerging and Innovative Public Transport and Technologies.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-04418

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Dawes, Margo
Zhao, Jinhua

Pagination:

18p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Identifier Terms:

Lyft; Uber

Subject Areas:

Highways; Planning and Forecasting; Policy; Public Transportation

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-04418

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 11:42AM