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Updated: Fri, 07/12/2024 - 12:16

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Alerte de McGill. Le campus du centre-ville restera partiellement fermé jusqu’au lundi 15 juillet, en soirée. Complément d’information : Direction de la protection et de la prévention

News

Identifying Perverse Incentives in Buyer Profiling on Online Trading Platforms

Published: 6 October 2021

Authors: K.N. Kannan, R.L. Saha and Warut Khern-am-nuai

Publication: Information Systems Research, Forthcoming

Abstract:

Consumer profiling has become one of the most common practices on online trading platforms. Many platforms strive to obtain and implement technological innovations that allow them to understand and identify consumers’ needs, and, thereafter, monetize this capability by charging sellers to present and/ or sell their products or services based on consumers’ interests. However, an interesting and relevant question arises in this context: Does the platform have an incentive to profile its buyers as accurately as possible? This paper develops and analyzes a parsimonious game-theoretic model to answer this research question. We find that, surprisingly, platforms that charge sellers for discoveries have a perverse incentive to deviate from accurate buyer profiling. However, such a perverse incentive does not exist for platforms that charge sellers for transactions. As a result, with such a perverse incentive, social welfare under discovery-based pricing is lower than that under transaction-based pricing.


Desautels 22

In recognition of research excellence as it relates to publications in top-tier management journals, our Faculty has compiled a list of high quality, peer-reviewed management journals, which is referred to as the Desautels 22.

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