Big Data and Competition Policy

Big Data and Big Analytics are a big deal today. Big Data is playing a pivotal role in many companies' strategic decision-making. Companies are striving to acquire a 'data advantage' over rivals. Data-driven mergers are increasing. These data-driven business strategies and mergers raise significant implications for privacy, consumer protection and competition law. At the same time, European and United States' competition authorities are beginning to consider the implications of a data-driven economy on competition policy. In 2015, the European Commission launched a competition inquiry into the e-commerce sector and issued a statement of objections in its Google investigation. The implications of Big Data on competition policy will likely be a part of the mix. Big Data and Competition Policy is the first work to offer a detailed description of the important new issue of Big Data and explains how it relates to competition laws and policy, both in the EU and US. The book helps bring the reader quickly up to speed on what is Big Data, its competitive implications, the competition authorities' approach to data-driven mergers and business strategies, and their current approach's strengths and weaknesses. Written by two recognized leading experts in competition law, this accessible work offers practical guidance and theoretical discussion of the potential benefits (including data-driven efficiencies) and concerns for the practitioner, policy maker, and academic alike.

1 - Introduction
2. - Defining Big Data
3. - Smartphones as an Example of how Big Data and Privacy Intersect
4. - The Competitive Significance of Big Data
5. - Why Haven't Market Forces Addressed Consumers' Privacy Concerns?
6. - The US's and EU's Mixed Record in Assessing Data-Driven Mergers
7. - Agencies Focus on What Is Measurable (Price), Which Isn't Always Important (Free Goods)
8. - Data-Driven Mergers Often Fall Outside Competition Policy's Conventional Categories
9. - Belief that Privacy Concerns Differ from Competition Policy Objectives
10. - Importance of Entry Barriers in Antitrust Analysis
11. - Entry Barriers Can Be Higher in Multi-Sided Markets, Where One Side Exhibits Traditional Network Effects
12. - Scale of Data Trial-and-Error, 'Learning-by-Doing' Network Effects
13. - Two More Network Effects: Scope of Data & Spill-over Effects
14. - Reflections on Data-Driven Network Effects
15. - Risk of Inadequate Merger Enforcement
16. - The Price of Weak Antitrust Enforcement
17. - Recognizing When Privacy and Competition Law Intersect
18. - Data-opoly: Identifying Data-Driven Exclusionary and Predatory Conduct
19. - Understanding and Assessing Data-Driven Efficiencies Claims
20. - Need for Retrospectives of Data-Driven Mergers
21. - More Coordination among Competition, Privacy and Consumer Protection Officials
22. - Conclusion