Big Data and Personalized Price Discrimination in EU Competition Law

Summary:

The phenomenon ‘algorithmic consumer price discrimination’ (ACPD) forms the focus of this paper. The practice of price discrimination is hardly a new phenomenon. However, the technological capacities of Big Data substantially enhance the ability of digital retailers to engage in much more precise, targeted and dynamic forms of price discrimination that were not previously possible.

This article seeks to critically examine these practices from the perspective of competition law through which we seek to evaluate ACPD by reference to two contrasting normative values: economic efficiency, on the one hand, and fairness or equity on the other.

Our concern is with EU competition law, the core tenets of which are set out in Articles 101 and 102 of the Treaty on the Functioning of the European Union (TFEU), focusing on whether ACPD would be regarded as unlawful under Article 102 TFEU, which prohibits ‘abuse’ by particularly powerful firms. Given that the fundamental concern of competition law, today, is principally to promote economic efficiency, our analysis begins by applying economic theory to the practice of ACPD to identify whether it enhances or diminishes economic efficiency. As we demonstrate in Section II, the incentives for firms to engage in ACPD often exist. We find that consumers are in the aggregate often better off, economically, when sellers can price discriminate in this way, thereby enhancing consumer surplus. However, this is not always the case. Furthermore, whether EU competition law is solely and exclusively concerned with economic efficiency, or whether it provides scope for non-efficiency based considerations in the application of its provisions, is a matter of debate. Accordingly, in Section III we evaluate ACPD by reference to its fairness or justice understood in three distinct ways.

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