Pricing a Digital Services Marketplace under Asymmetric Information

14 Pages Posted: 31 Jan 2018 Last revised: 27 Mar 2019

See all articles by Pavel Izhutov

Pavel Izhutov

Axio Inc.; Altos Platform; Stanford University

Haim Mendelson

Stanford University - Stanford Graduate School of Business

Date Written: January 24, 2018

Abstract

This paper addresses the pricing problem of an online service marketplace under asymmetric information. An example is an online learning platform such as Coursera that provides courses from suppliers (in this case, universities) to learners. We focus on the matching function of the marketplace whereby it engages in sequential search on behalf of a consumer using partially-observable consumer and supplier attributes. We develop the optimal pricing policies for a general distribution of the unobservable valuations. When these distributions are exponential, it is optimal to charge the same total fee for each match rather than engage in price discrimination, and this entire fee should be levied on the less elastic side of the marketplace.

Keywords: pricing, price discrimination, revenue management, multi-sided platforms, online marketplaces, matching, service systems, intermediation

JEL Classification: C61, D42, D82, L11, L81, L86

Suggested Citation

Izhutov, Pavel and Izhutov, Pavel and Mendelson, Haim, Pricing a Digital Services Marketplace under Asymmetric Information (January 24, 2018). Available at SSRN: https://ssrn.com/abstract=3108333 or http://dx.doi.org/10.2139/ssrn.3108333

Pavel Izhutov (Contact Author)

Axio Inc.

San Francisco, CA

Altos Platform ( email )

Stanford University ( email )

Stanford, CA 94305
United States

Haim Mendelson

Stanford University - Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States
650-725-8927 (Phone)
650-725-7979 (Fax)

HOME PAGE: http://https://www.gsb.stanford.edu/faculty-research/faculty/haim-mendelson

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