Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
MD6 - PF4: Freight markets and platform pricing
Time:
Monday, 27/June/2022:
MD 16:00-17:30

Session Chair: Donghao Zhu
Location: Forum 10


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Presentations

Centralized versus decentralized pricing controls for dynamic matching platforms

Ali Aouad1, Omer Saritac1, Chiwei Yan2

1London Business School; 2University of Washington

We examine the effect of centralization on platforms' pricing decisions in two-sided matching markets. We develop a stylized model that describes the platforms' dynamic matching and pricing process over a continuum of market participants, which is directly motivated by the design of ridehailing platforms. We provide a comprehensive analytical characterisation of the market equilibrium. Next, we develop a simulation-based framework to compare the social welfare under three operating models.



Posted price versus auction mechanisms in freight transportation marketplaces

Sungwoo Kim1, He Wang1, Xuan Wang2

1Georgia Tech, United States of America; 2HKUST Business School, Hong Kong

We consider a truckload transportation marketplace in which a platform serves an intermediary to match shippers, who pay for transportation services, with carriers, who get compensation for transporting the loads. The objective of the platform is to design pricing and allocation mechanisms to maximize its long-run average profit. In this paper, we analyze the performance of posted price, auction, and hybrid mechanisms (which combine posted price and auction mechanisms).



Platform information design: a queueing-theoretic approach to online freight matching

Donghao Zhu, Stefan Minner, Martin Bichler

Technical University of Munich, Germany

The decision to display information of the freight market's current state impacts revenue due to user abandonment. The implications of such a decision are not well understood in platforms for freight exchanges. We study which information design maximizes expected revenue. Queueing models with balking and reneging are applied, and the steady-state behavior of the underlying Markov chains is analyzed. We find that in large markets, showing state information is preferred.



 
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