Design of an Aggregated Marketplace Under Congestion Effects: Asymptotic Analysis and Equilibrium Characterization

Sharing Economy: Making Supply Meet Demand, edited by Ming. Hu., 2018

Columbia Business School Research Paper No. 18-42

64 Pages Posted: 8 Mar 2018

See all articles by Ying-Ju Chen

Ying-Ju Chen

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management

Costis Maglaras

Columbia Business School - Decision Risk and Operations

Gustavo Vulcano

Universidad Torcuato Di Tella - School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: March 1, 2018

Abstract

We study an aggregated marketplace where potential buyers arrive and submit requests-for-quotes (RFQs). There are n independent suppliers modeled as M/GI/1 queues that compete for these requests. Each supplier submits a bid that comprises of a fixed price and a dynamic target leadtime, and the cheapest supplier wins the order as long as the quote meets the buyer's willingness to pay. We characterize the asymptotic performance of this system as the demand and the supplier capacities grow large, and subsequently extract insights about the equilibrium behavior of the suppliers. We show that supplier competition results in a mixed-strategy equilibrium phenomenon that is significantly different from the centralized solution. In order to overcome the efficiency loss, we propose a compensation-while-idling mechanism that coordinates the system: each supplier gets monetary compensation from other suppliers during his idle periods. This mechanism alters suppliers' objectives and implements the centralized solution at their own will.

Keywords: aggregated marketplace, service competition, asymptotic analysis

Suggested Citation

Chen, Ying-Ju and Maglaras, Costis and Vulcano, Gustavo, Design of an Aggregated Marketplace Under Congestion Effects: Asymptotic Analysis and Equilibrium Characterization (March 1, 2018). Sharing Economy: Making Supply Meet Demand, edited by Ming. Hu., 2018; Columbia Business School Research Paper No. 18-42. Available at SSRN: https://ssrn.com/abstract=3132198

Ying-Ju Chen (Contact Author)

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

Costis Maglaras

Columbia Business School - Decision Risk and Operations ( email )

New York, NY
United States

Gustavo Vulcano

Universidad Torcuato Di Tella - School of Business ( email )

Avda Figueroa Alcorta 7350
Buenos Aires, CABA 1428
Argentina

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