Price customization and targeting in matching markets

Renato Gomes and Alessandro Pavan
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Renato Gomes: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Alessandro Pavan: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: We introduce a model of (platform-mediated) many-to-many matching in which agents' preferences are both vertically and horizontally differentiated. We first show how the model can be used to derive the profit-maximizing matching plans under customized pricing. We then investigate the implications for targeting and welfare of uniform pricing (be it explicitly mandated or induced by privacy regulation), preventing the platform from conditioning prices on agents' profiles. The model can be applied to study ad exchanges, online retailing, and media markets.

Keywords: Asymmetric information; Many-to-many matching; Platforms; Second- and third-degree price discrimination; Targeting; Uniform pricing (search for similar items in EconPapers)
Date: 2024-06-11
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Published in RAND Journal of Economics, 2024, 55 (2), pp.230-265. ⟨10.1111/1756-2171.12464⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04672444

DOI: 10.1111/1756-2171.12464

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