Data Science Seminar
Quantifying supply-demand imbalance in ridesharing systems
Alex Chin
Quantifying supply-demand imbalance in ridesharing systems
| When | Wednesday, November 2, 2022, 10:30 AM – 11:45 AM (MT) |
|---|---|
| Where | WEB 3780 |
Abstract
The status of the rider and driver distributions and how they interact in a two-sided marketplace has implications for market efficiency and policy-making. As such, accurately characterizing the supply-demand state of Lyft’s marketplace is a crucial task. I will describe how this task can be framed in terms of an asymmetric optimal transport problem that yields a multi-resolution view of the supply-demand state and how it varies both spatially and temporally. I will then discuss how this approach can be incorporated into applications such as policy optimization and machine learning prediction problems. Time permitting I will also discuss other science efforts we have at Lyft.
Speaker
Tags: society & policy
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