Segmenting Two-Sided Markets

12 Pages Posted: 21 Feb 2017

See all articles by Siddhartha Banerjee

Siddhartha Banerjee

Cornell University - School of Operations Research and Information Engineering

Sreenivas Gollapudi

Google Inc.

Kostas Kollias

Google Inc.

Kamesh Munagala

Duke University Department of Computer Science

Date Written: October 12, 2016

Abstract

Recent years have witnessed the rise of many successful e-commerce marketplaces like the Amazon marketplace, Uber, AirBnB, and Upwork, where a central platform mediates economic transactions between buyers and sellers. A common feature of many of these two-sided marketplaces is that the platform has full control over search and discovery, but prices are determined by the buyers and sellers. Motivated by this, we study the algorithmic aspects of market segmentation via directed discovery in two-sided markets with endogenous prices. We consider a model where an online platform knows each buyer/seller's characteristics, and associated demand/supply elasticities. Moreover, the platform can use discovery mechanisms (search/recommendation/etc.) to control which buyers/sellers are visible to each other. This leads to a segmentation of the market into pools, following which buyers and sellers endogenously determine market-clearing transaction prices within each pool. The aim of the platform is to maximize the resulting volume of transactions/welfare in the market. We develop efficient algorithms with provable guarantees under a variety of assumptions on the demand and supply functions. We also test the validity of our assumptions on demand curves inferred from NYC taxicab log-data, as well as show the performance of our algorithms on synthetic experiments.

Keywords: Online marketplaces, directed discovery mechanisms, market segmentation

Suggested Citation

Banerjee, Siddhartha and Gollapudi, Sreenivas and Kollias, Kostas and Munagala, Kamesh, Segmenting Two-Sided Markets (October 12, 2016). Available at SSRN: https://ssrn.com/abstract=2920034 or http://dx.doi.org/10.2139/ssrn.2920034

Siddhartha Banerjee (Contact Author)

Cornell University - School of Operations Research and Information Engineering ( email )

237 Rhodes Hall
Ithaca, NY 14853
United States

Sreenivas Gollapudi

Google Inc. ( email )

Kostas Kollias

Google Inc. ( email )

Kamesh Munagala

Duke University Department of Computer Science ( email )

100 Fuqua Drive
Durham, NC 27708-0204
United States

HOME PAGE: http://www.cs.duke.edu/~kamesh/

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