What Drives the Efficiency in Ridesharing Markets? Evidence from Austin, Texas

Al-Chanati, Motaz; Iyer, Vinayak

doi:10.2139/ssrn.3959363

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…We denote the dual variables corresponding to the three constraints in ( 4)-( 6) by 𝑤, 𝑢 𝑢 , and 𝑢 𝑜 , respectively. The pair of constraints ( 5) and ( 6) correspond to the 𝐿 1 -norm in (1). The constraint (5) represents under-supplied situations, with a non-negative slack w.r.t.…”

Section: Market State Diagnosticsmentioning

confidence: 99%

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A Unified Representation Framework for Rideshare Marketplace Equilibrium and Efficiency

Chin¹,

Qin²

2023

Preprint

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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 (supplyand 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.

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Section: Market State Diagnosticsmentioning

confidence: 99%

“…Some recent works cover algorithms for dispatch [9,12,24,25,29,34], repositioning [5,7,15,18,20], pricing [2,8,14,19,30], and incentives [23,28]. There have also been works focusing on investigations and analyses of the driving factors for rideshare market efficiency [1,11,13,17].…”

Section: Introductionmentioning

confidence: 99%