The thesis explores big data-driven mergers of the big tech companies, focusing on an analysis of EU competition law principles, tools and tests and their applicability in light of specific legal and economic properties of big data. This includes in particular the free provision of products and services in markets where big data plays a major role and the corresponding challenges for the price-based competition law in the absence of its main parameter of competition.
We explore to what extent has the EU Commission already addressed the properties of big data such as its volume, variety, velocity, value, its partially excludable and non-rivalrous nature and whether this had an effect on treating a merger as pro- or anti-competitive. Moreover, the distinct features of observed markets such as very pronounced (in)direct network effects, market-tipping and multi-sided structure of markets are considered to discuss the challenges for the definition of relevant markets and the assessment of market power. The thesis explores the various data-based theories of harm ranging from the strengthening of dominance in attention markets, loss of potential competition or innovation competition, big data as an essential input to compete to tying and bundling practices involving big data.
The thesis also considers data-specific remedies and possible efficiencies brought about with mergers involving the big tech companies that feature the element of big data. Recent proposals for ex ante regulation of gatekeepers active in digital markets and other initiatives for reforms of EU competition law are featured when discussing a competition law treatment of big data.
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