Competition Policy in a World of Big Data

S. Vezzoso
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引用次数: 3

Abstract

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, summarises 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 users behaviour, of increasing market concentration, and, finally, of enabling further abuses of market power.
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大数据时代的竞争政策
大数据是为社会和经济关系注入变革效应的重要现象。通过利用数学、计算机科学和互联网的协同能力,消费者、企业和机器产生了前所未有的大量数据,这些数据被收集、存储和分析。随着物联网的全面出现,更多的数据将被观察到,并从个人的日常活动和习惯中推断出来。大数据隐含的前景是,越来越有可能从不同来源收集的非结构化数据中获得有价值的见解。许多行业的公司越来越多地使用计算机算法和大量数据来处理分析和预测问题,从市场情报到战略管理和自动化决策。认识到大数据对广泛的人类互动产生直接和直接影响的潜力越来越大,政策圈内的对话开始关注如何将这一现象纳入竞争政策框架本身。虽然大数据可以增强竞争,改善产品供应,并创造一个更有效地分配资源的市场,但本章认为,竞争政策的设计者和执行者必须应对前所未有的与数据相关的挑战。本章首先描述了大数据价值链,特别强调了数据收集、存储和分析如何推动数字经济的许多多边商业模式,总结了数据作为一种经济资产的一些众所周知的特性,并为分析大数据对竞争过程的影响设置了框架。本章最后提出了竞争政策的一些初步含义。特别是,大数据可能会产生以下影响:使串通更加普遍、稳定和难以发现;通过增加依赖形式并可能限制平台间竞争和用户行为,重塑垂直供应链内的传统关系;增加市场集中度;最后,使市场力量进一步滥用成为可能。
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