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.
Rapid technological innovations have challenged the conventional application of antitrust and competition law across the globe. Acknowledging these challenges, this original work analyses the roles of innovation in competition law analysis and reflects on how competition and antitrust law can be refined and tailored to innovation.
The use of data in society has seen an exponential growth in recent years. Data science, the field of research concerned with understanding and analyzing data, aims to find ways to operationalize data so that it can be beneficially used in society, for example in health applications, urban governance or smart household devices. The legal questions that accompany the rise of new, data-driven technologies however are underexplored. This book is the first volume that seeks to map the legal implications of the emergence of data science. It discusses the possibilities and limitations imposed by the current legal framework, considers whether regulation is needed to respond to problems raised by data science, and which ethical problems occur in relation to the use of data. It also considers the emergence of Data Science and Law as a new legal discipline.
Across the globe, Google, Amazon, Facebook, Apple and Microsoft have accumulated power in ways that existing regulatory and intellectual frameworks struggle to comprehend. A consensus is emerging that the power of these new digital monopolies is unprecedented, and that it has important implications for journalism, politics, and society. It is increasingly clear that democratic societies require new legal and conceptual tools if they are to adequately understand, and if necessary check the economic might of these companies. Equally, that we need to better comprehend the ability of such firms to control personal data and to shape the flow of news, information, and public opinion. In this volume, Martin Moore and Damian Tambini draw together the world's leading researchers to examine the digital dominance of technologies platforms and look at the evidence behind the rising tide of criticism of the tech giants. In fifteen chapters, the authors examine the economic, political, and social impacts of Google, Amazon, Facebook, Apple, and Microsoft, in order to understand the different facets of their power and how it is manifested. Digital Dominance is the first interdisciplinary volume on this topic, contributing to a conversation which is critical to maintaining the health of democracies across the world.
"On September 18, 2017 the Competition Bureau (Bureau) released a discussion paper titled "Big data and Innovation: Implications for Competition Policy in Canada". Consistent with its commitment to engage with stakeholders on important areas of public policy, that paper was meant to prompt discussion on how big data should affect competition law enforcement under the Competition Act (Act). To facilitate this discussion, the Bureau solicited public comments on its website and engaged with stakeholders in a variety of international and domestic fora. This document is a synthesis of key themes revealed in the Bureau's review of this important topic informed by this feedback"--Introd., p. 4.
This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics.