Understanding working time and relocation choices of ridehailing drivers
Yuanjie Tu, Moein Khaloei, Natalia Zuniga-Garcia, Don MacKenzie
TL;DR
This paper classifies ridehailing drivers into four types and models their working time and relocation decisions using survey data from 200 drivers in Seattle.
Contribution
It introduces a joint modeling approach for driver working time and relocation choices based on a new survey dataset.
Findings
Identification of four driver types
Insights into driver decision-making patterns
Quantitative analysis of relocation and working time choices
Abstract
We identified four types of ridehailing drivers and jointly modeled driver working time and relocation choices using a stated preference survey of 200 drivers in Seattle, US.
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Taxonomy
TopicsTransportation and Mobility Innovations · Urban Transport and Accessibility · Transportation Planning and Optimization