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Activity Number: 556 - Causal Inference for Complex Data Challenges
Type: Invited
Date/Time: Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
Sponsor: SSC (Statistical Society of Canada)
Abstract #309292
Title: Causal Inference at Large Scale Ride-Hailing Two Sided Platforms
Author(s): SHIKAI LUO*
Companies: Didi Chuxing
Keywords: Two Sided Market; Interference; Spatiotemporal; Functional Data

Classical design of experiments are not applicable at ride-hailing platforms, like Uber, Lyft and DiDi, since such two sided markets are highly spatiotemporal, and correlations are everywhere. Experiment units are not independent with each other, riders share the same pool of drivers, and drivers share the same pool of riders. In this talk, we will talk about the novel designs of experiments for key platform strategies (order dispatch, driver repositioning, riders' promotions, and drivers' incentives), and how we analyze the results using causal inference.

Authors who are presenting talks have a * after their name.

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