Monopoly Pricing in the Presence of Social Learning

Management Science 63, 3586–3608.

50 Pages Posted: 24 Nov 2011 Last revised: 2 Jan 2018

See all articles by Davide Crapis

Davide Crapis

Columbia Business School - Decision Risk and Operations

Bar Ifrach

Uber Technologies Inc. - Uber Freight

Costis Maglaras

Columbia Business School - Decision Risk and Operations

Marco Scarsini

LUISS, Dipartimento di Economia e Finanza

Date Written: December 6, 2015

Abstract

A monopolist offers a product to a market of consumers with heterogeneous quality preferences. Although initially uninformed about the product quality, they learn by observing past purchase decisions and reviews of other consumers. Our goal is to analyze the social learning mechanism and its effect on the seller's pricing decision. Consumers follow an intuitive, non-Bayesian decision rule. Under conditions that we identify, we show that consumers eventually learn the product's quality. We show how the learning trajectory can be approximated in settings with high demand intensity via a mean-field approximation that highlights the dynamics of this learning process, its dependence on the price, and the market heterogeneity with respect to quality preferences. Two pricing policies are studied: a static price, and one with a single price change. Finally, numerical experiments suggest that pricing policies that account for social learning may increase revenues considerably relative to policies that do not.

Keywords: social learning, information aggregation, bounded rationality, optimal pricing

JEL Classification: D49, D83

Suggested Citation

Crapis, Davide and Ifrach, Bar and Maglaras, Costis and Scarsini, Marco, Monopoly Pricing in the Presence of Social Learning (December 6, 2015). Management Science 63, 3586–3608.. Available at SSRN: https://ssrn.com/abstract=1957924 or http://dx.doi.org/10.2139/ssrn.1957924

Davide Crapis

Columbia Business School - Decision Risk and Operations ( email )

New York, NY
United States

HOME PAGE: http://www.columbia.edu/~dc2792/

Bar Ifrach (Contact Author)

Uber Technologies Inc. - Uber Freight ( email )

685 Market Street
San Francisco, CA 94105
United States

Costis Maglaras

Columbia Business School - Decision Risk and Operations ( email )

New York, NY
United States

Marco Scarsini

LUISS, Dipartimento di Economia e Finanza ( email )

Viale Romania 32
Rome, RM 00197
Italy

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