A Unified Representation Framework for Rideshare Marketplace Equilibrium and Efficiency
This work addresses the challenge of analyzing market efficiency for ridesharing platforms, which is incremental as it builds upon an existing metric.
The paper tackles the problem of quantifying supply-demand balance in ridesharing marketplaces by developing SD-GEM, a dual-perspective representation based on the graph-based equilibrium metric (GEM), and proposes statistical tests to measure efficiency improvements and explain underlying factors.
Ridesharing platforms are a type of two-sided marketplace where ``supply-demand balance'' is critical for market efficiency and yet is complex to define and analyze. We present a unified analytical framework based on the graph-based equilibrium metric (GEM) for quantifying the supply-demand spatiotemporal state and efficiency of a ridesharing marketplace. GEM was developed as a generalized Wasserstein distance between the supply and demand distributions in a ridesharing market and has been used as an evaluation metric for algorithms expected to improve supply-demand alignment. Building upon GEM, we develop SD-GEM, a dual-perspective (supply- and demand-side) representation of rideshare market equilibrium. We show that there are often disparities between the two views and examine how this dual-view leads to the notion of market efficiency, in which we propose novel statistical tests for capturing improvement and explaining the underlying driving factors.