TY - JOUR
T1 - Ridesharing in Adelaide
T2 - Segmentation of users
AU - Soltani, Ali
AU - Allan, Andrew
AU - Khalaj, Fahimeh
AU - Pojani, Dorina
AU - Mehdizadeh, Milad
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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.
KW - Adelaide
KW - Australia
KW - Ridesharing
KW - Sharing mobility
KW - Uber
UR - http://www.scopus.com/inward/record.url?scp=85103665368&partnerID=8YFLogxK
U2 - 10.1016/j.jtrangeo.2021.103030
DO - 10.1016/j.jtrangeo.2021.103030
M3 - Article
AN - SCOPUS:85103665368
SN - 0966-6923
VL - 92
JO - Journal of Transport Geography
JF - Journal of Transport Geography
M1 - 103030
ER -