Finding the Subway Disruption Regimes of Switching Subway to Uber in Toronto. Issue 12 (December 2020)

• Record Type: Journal Article
• Authors: Hawkins, Jason; Habib, Khandker Nurul
• Is Part Of: Transportation research record. Volume 2674:Issue 12(2020)
• Page Start: 303
• Page End: 311
• Publication Date: 2020-12
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198120953797
• Languages: English
• ISSNs: 0361-1981

Abstract

The evolving relationship between public transit and transportation network companies (TNCs), such as Uber and Lyft, is of great interest to government agencies and has seen much critical attention in the academic literature. In this paper, we focus on the demand for TNC trips (also known as ride-hailing trips) during the disruption of the subway service. We combined a detailed dataset of Uber trips made in Toronto, Canada during the period September 2016 to August 2018 and subway disruption data provided by the Toronto Transit Commission. These data were used to examine the question: how long are subway users willing to wait during a disruption before switching modes? This question was framed as a threshold point, and an innovative structural threshold regression model was used to obtain an answer. Controlling for environmental and location-specific factors in the model, it was revealed that subway users in Toronto tend to switch to Uber after a service delay of as little as 3 min, with an average result of 7 min and an upper bound of 12 min.