The rise of big data and stellar progress in machine-learning techniques, powered by artificial intelligence (AI), have enabled the unprecedented rise of a few superstar firms in the past twenty years (also known as big tech). Not coincidentally, all these firms are active on markets that share a common characteristic: they are data driven. We will delineate such markets from traditional markets and study their economic peculiarities, which allows the largest firm to tip a market towards monopoly in the long run and to earn extremely high profits. In this IOEA lecture implications for innovation and welfare will be studied, just as possible and actual policy interventions, also in the light of ongoing regulatory initiatives in various countries. The lecture builds on five research papers that, methodologically, combine game-theoretic analysis, experiments with a search engine, a discrete-choice experiment, and economic governance theory to design efficient institutions solving the identified policy problems.

Prüfer, Jens and Christoph Schottmüller (2021), “Competing with Big Data,” Journal of Industrial Economics, 69: 967-1008.

Graef, Inge and Jens Prüfer (2021), “Governance of Data Sharing: a Law & Economics Proposal,” Research Policy, 50: 104330.

Klein, Tobias, Kurmangaliyeva, Madina, Jens Prüfer and Patricia Prüfer (2025), “How important are user-generated data for search-result quality? Experimental evidence,” Journal of Law & Economics, 68(3).