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Pricing and Matching in the Sharing ...

Zhou, Yun.

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Pricing and Matching in the Sharing Economy.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pricing and Matching in the Sharing Economy./
Author:	Zhou, Yun.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	132 p.
Notes:	Source: Dissertations Abstracts International, Volume: 79-08, Section: A.
Contained By:	Dissertations Abstracts International79-08A.
Subject:	Operations research. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10633504
ISBN:	9780355532111

Pricing and Matching in the Sharing Economy.
Zhou, Yun.

Pricing and Matching in the Sharing Economy. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 132 p.

Source: Dissertations Abstracts International, Volume: 79-08, Section: A.

Thesis (Ph.D.)--University of Toronto (Canada), 2017.

This item must not be sold to any third party vendors.

We study operational problems related to the sharing economy. Sharing economy platforms such as Uber offer the crowdsourced suppliers a wage for providing services/goods, and charge the customers a price for using them. In Chapter 2, we study the fixed commission rate contract practiced by many sharing economy platforms. We show that by using the optimal flat-commission contract, the platform achieves at least 75% of the optimal profit of the first-best benchmark, in which the platform freely chooses the price and wage under various market conditions. In Chapter 3, we consider a platform's problem of dynamically matching random demand and supply of heterogeneous types in a periodic-review fashion. The platform decides the optimal matching policy to maximize the total discounted rewards minus costs. We provide sufficient and robustly necessary conditions only on matching rewards such that the optimal matching policy follows a priority hierarchy among possible matching pairs. In Chapter 4, we study the dynamic matching problem in Chapter 3 under two specific forms of reward structures. First, we consider the problem with horizontally differentiated supply and demand types. In that problem, supply and demand types locate on a unidirectional circle. The unit matching reward between a supply type j and a demand type i is a decreasing function with respect to the unidirectional distance from the location of j to that of i on the circle. We then study the problem with vertically differentiated supply and demand types, for which we impose a reward structure in which types have "quality" differences. For both cases, we apply the results in Chapter 3 to characterize the optimal matching policy. In Chapter 5, we study the pricing behaviors of two agents under incentives generated from social comparison. We demonstrate how opposite-directional social comparisons interact with demand variability to change competitive behaviors. In particular, we show that the stronger the behind aversion behavior, the more intense the price competition, and that there is a threshold on the market variability above which price competition is more alleviated and below which price competition is more intensified, when the agents exhibit stronger ahead-seeking behavior.

ISBN: 9780355532111Subjects--Topical Terms:

547123
Operations research.
Subjects--Index Terms:

Matching

Pricing and Matching in the Sharing Economy.
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300 $a 132 p.
500 $a Source: Dissertations Abstracts International, Volume: 79-08, Section: A.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Hu, Ming.
502 $a Thesis (Ph.D.)--University of Toronto (Canada), 2017.
506 $a This item must not be sold to any third party vendors.
520 $a We study operational problems related to the sharing economy. Sharing economy platforms such as Uber offer the crowdsourced suppliers a wage for providing services/goods, and charge the customers a price for using them. In Chapter 2, we study the fixed commission rate contract practiced by many sharing economy platforms. We show that by using the optimal flat-commission contract, the platform achieves at least 75% of the optimal profit of the first-best benchmark, in which the platform freely chooses the price and wage under various market conditions. In Chapter 3, we consider a platform's problem of dynamically matching random demand and supply of heterogeneous types in a periodic-review fashion. The platform decides the optimal matching policy to maximize the total discounted rewards minus costs. We provide sufficient and robustly necessary conditions only on matching rewards such that the optimal matching policy follows a priority hierarchy among possible matching pairs. In Chapter 4, we study the dynamic matching problem in Chapter 3 under two specific forms of reward structures. First, we consider the problem with horizontally differentiated supply and demand types. In that problem, supply and demand types locate on a unidirectional circle. The unit matching reward between a supply type j and a demand type i is a decreasing function with respect to the unidirectional distance from the location of j to that of i on the circle. We then study the problem with vertically differentiated supply and demand types, for which we impose a reward structure in which types have "quality" differences. For both cases, we apply the results in Chapter 3 to characterize the optimal matching policy. In Chapter 5, we study the pricing behaviors of two agents under incentives generated from social comparison. We demonstrate how opposite-directional social comparisons interact with demand variability to change competitive behaviors. In particular, we show that the stronger the behind aversion behavior, the more intense the price competition, and that there is a threshold on the market variability above which price competition is more alleviated and below which price competition is more intensified, when the agents exhibit stronger ahead-seeking behavior.
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