Efficient Matchmaking in Assignment Games with Application to Online Platforms

44 Pages Posted: 8 Mar 2020 Last revised: 2 Oct 2020

See all articles by Peng Shi

Peng Shi

University of Southern California - Marshall School of Business

Date Written: June 22, 2020

Abstract

Online platforms that match customers with service providers utilize a wide variety of designs: some implement a searchable directory of one side of the market (i.e., Airbnb, Google Local Services); some allow both sides of the market to search and initiate contact (i.e., Upwork, Care.com); others implement centralized matching (i.e., Uber, Lyft, Amazon Home Services). This paper provides prescriptive guidelines on the optimal platform design for any given market, and sheds light on why matchmaking seems to be harder in certain industries than in others. The insights are derived from analyzing the assignment game of Shapley and Shubik (1971) using concepts from communication complexity theory (Kushilevitz and Nisan 2006).

Keywords: market design, online platforms, two-sided matching, communication complexity

JEL Classification: D47, D83, C78

Suggested Citation

Shi, Peng, Efficient Matchmaking in Assignment Games with Application to Online Platforms (June 22, 2020). USC Marshall School of Business Research Paper, Available at SSRN: https://ssrn.com/abstract=3536086 or http://dx.doi.org/10.2139/ssrn.3536086

Peng Shi (Contact Author)

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA California 90089
United States

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