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Algorithms, Big Data, and Merger Control

  • 2022
  • OriginalPaper
  • Chapter
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Abstract

The chapter delves into the increasing focus on digital competition and the underenforcement of merger control in the digital sector. It discusses the challenges competition authorities face in evaluating mergers involving algorithm-driven businesses, including the lack of technical expertise and the complexities of multi-sided markets. The text catalogs cases where algorithms and data have been critical to the competitive assessment of mergers and explores both horizontal and non-horizontal theories of harm. It also discusses the shift towards dynamic theories of harm, such as 'killer acquisitions,' and the future challenges and potential reforms in this area. The chapter provides a detailed analysis of the decisional practice of the European Commission and the UK’s Competition and Markets Authority, making it an essential read for those interested in the intersection of competition law, technology, and policy.

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Title
Algorithms, Big Data, and Merger Control
Authors
Verity Egerton-Doyle
Jonathan Ford
Copyright Year
2022
DOI
https://doi.org/10.1007/978-3-030-85859-9_4
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