Algorithmic Price Personalization: From Laesio Enormis to Laesio Algorithmica?

Abstract

Of the many concerns triggered by the rapid growth of digital commerce and the expansion of the data-based economy, price personalization occupies a prominent yet peculiar position. For many firms, the availability of big data and refined algorithmic tools has opened unprecedented avenues to learn about consumers’ financial and personal standing, market preferences, and transactional behaviour patterns. Building on these insights, firms have (at least to some degree) obtained an ability to make behavioural predictions about the future conduct of their clients, including their interest in a particular assortment of products, responsiveness to certain forms of advertising, and – not least importantly – their willingness to pay a certain price. This practice, commonly referred to as price personalization or price discrimination, is becoming an increasingly widespread business model in the online economy.

The text is an introduction to the Cambridge Handbook on Algorithmic Price Personalization and the Law, edited by F. Esposito and M. Grochowski. The volume contains contributions from a multidisciplinary group of scholars with substantial expertise in legal, economic, data-science, and marketing research on consumer prices. The authors, from various European and non-European jurisdictions, have different perspectives on personalized prices. The plurality of voices collected in the Handbook stimulates readers to form their own opinions and join the collective reflection on what, if anything, the law should do about algorithmic price personalization. The structure of the Handbook rests on three interdependent parts, each containing chapters by experts from law and other social sciences.

Keywords: price, price personalization, consumer law, algorithms, personal data, antitrust

JEL Classification: K10, K12, K21