Shared mobility adoption from 2016 to 2018 in the Greater Toronto and Hamilton Area: Demographic or geographic diffusion?

Abstract

Shared mobility services, such as on-demand ride-hailing, car sharing, and bike sharing, have significantly expanded the mobility tools available to urban residents. Understanding how these technologies are adopted over time is critical towards developing appropriate transportation policy measures. Most fundamentally: is adoption over time driven by demographic or geographic diffusion or a combination of the two? This study uses 2016 and 2018 survey data to explore the demographic and spatial predictors of changes in the adoption of on-demand ride-hailing, car sharing, and bike sharing in the Greater Toronto and Hamilton Area (GTHA) in Ontario, Canada.This study uses both descriptive statistics and inferential models to identify changes in the adoption process between 2016 and 2018. Trivariate ordered models estimated using diagonally weighted least squares (DWLS) suggest that spatial diffusion plays a role (accounting for 9–44% of changes in adoption between 2016 and 2018), that joint demographic-spatial patterns explain some variation in adoption over time (4–11%), but that demographic controls explain most changes in adoption over time (approximately 39–49%). Notably, adoption is concentrated (albeit somewhat less so over time) among younger cohorts, and it increases among women, among larger households, and among households without children. It is unclear how these changes in adoption will be impacted by the Covid-19 pandemic and future studies should explore the non-linear and complex nature of technology adoption, including the relative roles of service supply and demand changes.