Selling through online marketplaces with consumer profiling

Xing, Xinjie ORCID: 0000-0001-6277-5045, Huang, Hongfu and Hedenstierna, Carl Philip T ORCID: 0000-0002-0382-1387
(2023) Selling through online marketplaces with consumer profiling. Journal of Business Research, 164. p. 114022.

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Retail platforms obtain consumers’ individual preferences by gathering vast amounts of data and can deliver such information to online retailers to support their pricing activities; this is called consumer-profiling services (CPS). We develop a game-theoretic model to study how a retail platform should provide CPS in light of retailers’ competition and consumers’ data-blocking activities. We show that exclusively providing data to high-quality retailers results in a net benefit for the platform and retailers. Low-quality retailers benefit from refusing the CPS provided by the platform to avoid head-to-head competition. In addition, we find that consumers’ data blocking can benefit both the platform and retailers when the data-blocking cost is moderate, which is counterintuitive. We also find that data blocking always hurts consumer surplus and social welfare. To test the robustness of the main model, three extensions are discussed: sequential pricing, asymmetric production costs, and positive service fees.

Item Type: Article
Uncontrolled Keywords: Retail platforms, Consumer profiling services, Data blocking, Competition, Pricing
Divisions: Faculty of Humanities and Social Sciences > School of Management
Depositing User: Symplectic Admin
Date Deposited: 23 May 2023 08:03
Last Modified: 23 Jun 2023 09:25
DOI: 10.1016/j.jbusres.2023.114022
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