- JRC nr: JRC122896
- 10 Februar 2021
This paper starts with some basic economic characteristics of data that distinguish them from ordinary goods and services, including non-excludability and non-rivalry, economies of scope in data re-use and aggregation, the social value of data and their role in generating network effects. It explores how these characteristics contribute to the emergence of large digital platforms that generate a combination of positive and negative welfare effects for society, including data-driven network effects. It distinguishes between lexicographic and probabilistic data-driven matching in networks. Both may lead to market “tipping”. It emphasizes the social value of data and the positive and negative social externalities that may come with this. Platforms are necessary intermediaries to generate the social welfare or network externalities from data. However, the economic role of data-driven platforms is ambivalent. On the one hand, platforms enable society to benefit from positive externalities in data collection via economies of scale and scope in data aggregation of transactions and interactions across users, both firms and consumers. That gives them a privileged market overview that none of the individual users has. Platforms can use this information asymmetry to facilitate interaction and increase welfare for users. These data externalities attract users to the platform. On the other hand, data-driven network effects may result in monopolistic market power of platforms which they can use for their own benefit, at the expense of users. Any policy intervention that seeks to address the market power of online platforms requires careful balancing between these two poles. Finally, the paper briefly discusses ecosystems that leverage data to coordinate interactions between different platforms.