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A General Matching Theory of Ride-Hail.
~
Chen, Hongyu.
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A General Matching Theory of Ride-Hail.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
A General Matching Theory of Ride-Hail./
作者:
Chen, Hongyu.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:
96 p.
附註:
Source: Dissertations Abstracts International, Volume: 82-06, Section: B.
Contained By:
Dissertations Abstracts International82-06B.
標題:
Transportation. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28156834
ISBN:
9798698575856
A General Matching Theory of Ride-Hail.
Chen, Hongyu.
A General Matching Theory of Ride-Hail.
- Ann Arbor : ProQuest Dissertations & Theses, 2020 - 96 p.
Source: Dissertations Abstracts International, Volume: 82-06, Section: B.
Thesis (Ph.D.)--Northwestern University, 2020.
This item must not be sold to any third party vendors.
Mobile internet has brought a disruptive innovation to the ride-hail industry. The technology introduced by Uber, referred to as e-hail, matches passengers with drivers through their smart phones, while integrating transaction and feedback in a single app. In comparison to taxis hailed off street, or street-hail (s-hail hereafter), e-hail has been widely praised for not only improving user experience, but also boosting productivity. This dissertation focuses on deepening our understanding on the nature and limit of both ride-hail modes by proposing a general matching theory of ride-hail.This theory, along with calibration methods and empirical evidences, not only shows that the passenger-driver matching process in ride-hail is indeed dictated by two primary physical limitations: the passengers' ability to access distant vacant vehicles and the drivers' (or the platform's) preference for certain locations, but further discovers that the revolution of e-hail is a tale of two markets:On the one hand, by expanding passengers' access to vacant vehicles and vice versa, e-hail dramatically improves matching efficiency. In low-density markets particularly, where both demand and supply for ride-hail are low, this advantage substantially lowers the likelihood of unpleasantly long waits. On the other hand, connecting a large number of waiting passengers to the same pool of unmatched vacant vehicles induces competition among passengers, which severely limits e-hail's ability to exploit economies of scale in matching. The impact of this loss in scalability with e-hail will become more prominent in high-density markets, where arguably efficiency matters the most.
ISBN: 9798698575856Subjects--Topical Terms:
555912
Transportation.
Subjects--Index Terms:
Economy of scale
A General Matching Theory of Ride-Hail.
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Mobile internet has brought a disruptive innovation to the ride-hail industry. The technology introduced by Uber, referred to as e-hail, matches passengers with drivers through their smart phones, while integrating transaction and feedback in a single app. In comparison to taxis hailed off street, or street-hail (s-hail hereafter), e-hail has been widely praised for not only improving user experience, but also boosting productivity. This dissertation focuses on deepening our understanding on the nature and limit of both ride-hail modes by proposing a general matching theory of ride-hail.This theory, along with calibration methods and empirical evidences, not only shows that the passenger-driver matching process in ride-hail is indeed dictated by two primary physical limitations: the passengers' ability to access distant vacant vehicles and the drivers' (or the platform's) preference for certain locations, but further discovers that the revolution of e-hail is a tale of two markets:On the one hand, by expanding passengers' access to vacant vehicles and vice versa, e-hail dramatically improves matching efficiency. In low-density markets particularly, where both demand and supply for ride-hail are low, this advantage substantially lowers the likelihood of unpleasantly long waits. On the other hand, connecting a large number of waiting passengers to the same pool of unmatched vacant vehicles induces competition among passengers, which severely limits e-hail's ability to exploit economies of scale in matching. The impact of this loss in scalability with e-hail will become more prominent in high-density markets, where arguably efficiency matters the most.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28156834
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