Ridesharing in Adelaide: Segmentation of users

Ridesharing and the tech companies that enable it have become household names. However, as research has focused on users rather than non-users, much less is known about the latter. Understanding the characteristics, behaviours, and motivations of non-users is quite important too, if the planning goa...

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Bibliographic Details
Published inJournal of transport geography Vol. 92; p. 103030
Main Authors Soltani, Ali, Allan, Andrew, Khalaj, Fahimeh, Pojani, Dorina, Mehdizadeh, Milad
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.04.2021
Elsevier BV
Subjects
Adelaide
Australia
Car pools
Ethnic factors
Housing
Population density
Ridesharing
Security
Segmentation
Sharing mobility
Smartphones
Socioeconomics
Statistical analysis
Uber
Urban populations
Uber
Sharing mobility
Australia
Ridesharing
Adelaide
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Summary:Ridesharing and the tech companies that enable it have become household names. However, as research has focused on users rather than non-users, much less is known about the latter. Understanding the characteristics, behaviours, and motivations of non-users is quite important too, if the planning goal is to shift urban populations from private cars to ridesharing. This study examines both users and non-users in the context of Adelaide, an Australian metropolis of 1.3 million inhabitants. We segment (potential) ridesharers into three groups: (1) users, (2) interested non-users, and (3) non-interested non-users in order to investigate the determinants of their behaviours and preferences in more detail. Applying advanced statistical analyses, we find that population density and housing value at neighbourhood level, higher levels of education and income, causal work status, younger age, and access to smartphones are the key factors associated with higher ridesharing use and/or higher interest in ridesharing. Factors such as concern over safety and security, advanced age, digital illiteracy, and suburban living lead non-interested non-users to shun ridesharing. Socio-demographic factors such as car ownership, ethnic background; gender, and household size, are not associated with ridesharing behaviours or preferences. We conclude that the choice of ridesharing in Adelaide is driven by the notion of socio-economic status.
ISSN:0966-6923
1873-1236
DOI:10.1016/j.jtrangeo.2021.103030