Optimal Non-Linear Pricing with Data-Sensitive Consumers

The paper presented in this Mannheim Virtual IO Seminar introduces consumers with intrinsic privacy preferences into the monopolistic non-linear pricing model. Next to classical consumers, there is a share of data-sensitive consumers who refrain from buying if their purchase reveals information about their valuation to the monopolist. When the monopolist observes consumers’ privacy preferences, data-sensitive consumers obtain a pooling schedule, while classical consumers obtain the standard non-linear pricing schedule. Data-sensitive consumers with a low valuation obtain a strictly higher utility than classical consumers with the same valuation. By contrast, when privacy preferences are consumers’ private information, classical consumers obtain a higher utility than data-sensitive consumers with the same valuation. Data-sensitive consumers and the monopolist are worse off when privacy preferences are private information, whereas classical consumers are better off. The results are relevant for policy measures that target the data-awareness of consumers, such as the European GDPR.