Big data is an important phenomenon injecting transformative effects into social and economic relationships. Consumers, firms and machines produce unprecedented amounts of data collected, stored and analysed by leveraging the synergic capabilities of mathematics, computer science and the Internet. With the full advent of the Internet of Things, even more data will be observed about, and inferred from, individuals’ everyday activities and habits. The implied promise of big data is that it is increasingly possible to gain valuable insights out of unstructured data collected from different sources. Firms in many industries are increasingly using computer algorithms and big quantities of data to handle problems of analysis and prediction, from market intelligence to strategic management and automated decision-making. Acknowledging the growing potential for big data to have an immediate and direct impact on a broad range of human interactions, conversations within policy circles are starting to focus on how this phenomenon should factor into the competition policy framework itself. While big data can enhance competition, improve product offerings and create a marketplace where resources are allocated more efficiently, the chapter argues that competition policy designers and enforcers are bound to deal with unprecedented data-related challenges. The chapter starts with a description of the big data value chain, highlights in particular how data collection, storage and analysis are driving many of the multisided business models of the digital economy, summarizes some well-known peculiarities of data as an economic asset and sets the framework for the analysis of the effects of big data on competition processes. The chapter concludes by drawing a few preliminary implications for competition policy. In particular, big data could have the effect of making collusion more prevalent, stable and difficult to detect, of reshaping traditional relationships within a vertical supply chain by increasing forms of dependency and potentially restraining inter-platform competition and user behaviour, of increasing market concentration, and, finally, of enabling further abuses of market power.
Algorithms are the fundamental ingredient of online businesses such as search engines, marketplaces, peer-to-peer platforms and social networks. Whereas the issues of algorithmic transparency and accountability are common to other areas of law and policy, there are further and more specific implications for competition policy. Against the background of increasingly algorithm-based markets, the chapter explores the potential of the notion of ‘competition by design’, as broadly derived from the related concept of ‘data protection by design’, which is enshrined in the General Data Protection Regulation. EU Competition Commissioner Margarethe Vestager made clear that firms applying algorithms need to think from the start about how to keep them compliant with competition law (‘algorithms will have to go to law school before they are let out’). The chapter concludes that algorithm design thinking could be a promising new tool at the disposal of competition authorities in the digital economy.
Online platforms have come to play an increasingly important role in hotel room bookings. Online travel agents (OTAs) have imposed so-called rate parity clauses in the contracts with their hotel partners. These are contract clauses laying down the hotelier’s obligation to display the same room prices across sales channels. Within the European Union, different national competition authorities have reacted differently to the anticompetitive nature of such clauses. The main contribution of this chapter consists in highlighting those diverse approaches and in outlining some of challenges of applying traditional competition law enforcement tools to rate parity clauses.