Surge Pricing and Labor Supply in the Ride-Sourcing Market

Abstract

This study proposes equilibrium models under different behavioral assumptions of labor supply in a ride-sourcing market and then investigates the performance of surge pricing. A time-expanded network is first proposed to delineate possible work schedules of drivers. Based on the proposed network, we provide formulations and algorithms for both neoclassical and income-targeting hypotheses to characterize the labor supply of ride-sourcing drivers, i.e., their choices of work hours. We then investigate the impact of surge pricing using a bi-level programing framework, with the lower-level problem capturing the equilibrium work hour choices while the upper-level one representing revenue-maximizing surge pricing. Compared to static pricing, the platform and drivers in general enjoy higher revenue while customers may be made worse off during highly surged periods. A simple regulation scheme to reduce market power is discussed.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 161 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.