Learning Match Quality

27 Pages Posted: 23 Mar 2023

See all articles by Arthur Fishman

Arthur Fishman

Bar-Ilan University - Department of Economics

Vikram Ahuja

Indiana University - Kelley School of Business - Department of Business Economics & Public Policy

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Abstract

For many new products or products with multiple attributes, learning the price is often easier than learning one's willingness to pay. We model a market in which consumers face a transportation cost to discover a seller's price, and then have the option to pay a learning cost to discover the product's match value before deciding whether to purchase or continue searching. In equilibrium each seller optimally sets either a "regular" price which induces a visiting consumer to learn or a sufficiently low "preemption" price which induces the consumer to accept immediately. In contrast to the common intuition about search frictions, we find that higher learning costs can improve consumer welfare by increasing sellers' incentive to preempt, which lowers prices and increases sales. We also demonstrate that the incentive to preempt is lower in a monopoly than in an oligopoly, and in a uniform example show that welfare and consumer surplus are higher in a monopoly for a range of learning costs. From a platform design perspective, we find that consumers are better off from clear disclosure for products with low learning costs and from obfuscation for products with high learning costs.

Keywords: search, learning match value, learning costs, preemption price, Obfuscation

Suggested Citation

Fishman, Arthur and Ahuja, Vikram, Learning Match Quality. Available at SSRN: https://ssrn.com/abstract=4397764 or http://dx.doi.org/10.2139/ssrn.4397764

Arthur Fishman (Contact Author)

Bar-Ilan University - Department of Economics ( email )

Ramat-Gan, 52900
Israel
972-3-531-8366 (Phone)
972 3 535 3180 (Fax)

Vikram Ahuja

Indiana University - Kelley School of Business - Department of Business Economics & Public Policy ( email )

Bloomington, IN 47405
United States

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