Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 17, 2018 erstellt
Description:
Users' data has become a crucial production factor for companies and a necessary asset if they are to compete in the digital ecosystem. However, users' data is a production factor that is not mobile across companies, since a company can only use the data that its customers—its “users”— generate within its own environment and not the data that its users produce outside of it. This represents a market friction that hinders competition, leads to monopolies, and raises the entry barriers for new companies. Additionally, the users generating and owning the data stored in a company have no control over or overview of their data and cannot monetize it. We model the users' data as a production factor in the value generation function of companies and introduce the concept of data elasticity of value. Further, and in light of advances in distributed database management, blockchain technology, and data protection regulation, we propose an information system that allows users to sell their data freely to companies other than those within which the data was generated, receiving a self-generated, market-driven basic income. A consequence of this system is that data becomes a mobile production factor, since any company can work with the data that its users generate outside of that company's own environments. Moreover, our system solves some of the data- ownership problems of the current Internet business model, lowers the entry barriers for new data-intensive companies, and enables new income streams for data-intensive companies, which in the case of online platforms allows them to avoid a dependence on online advertisement to finance their operations. We propose this ecosystem at a conceptual level and simulate the impact of companies having access to higher fractions of their users' data under different data elasticities of value. We show that the introduction of such a system could theoretically, and under the taken assumptions, more than double the aggregated value of data-intensive companies