Fickle Fingers: Ride-Hail Surge Factors and Taxi Bookings
49 Pages Posted: 25 Apr 2018 Last revised: 24 Jun 2020
Date Written: March 26, 2019
We study the role of ride-hailing surge factors on the allocative efficiency of taxis by combining a reduced form estimation with structural analyses using machine-learning-based demand predictions. We estimate an upper-bound of the cross-price elasticity of taxi bookings to surge factors of only 0.26, but incorporating surge factors into a demand-prediction model improves the out-of-sample accuracy by 12-15%. Our structural analyses based on a driver guidance system finds the improved accuracy reduces drivers' vacant roaming times by 9.4% and increases average trips per taxi by 2.3%, suggesting the price information is valuable across platforms, even if elasticities are low.
Keywords: transportation economics, surge pricing, consumer behavior, big data analytics
JEL Classification: C53, D12, D47, R41
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