Regulation of Data-driven Market Power in the Digital Economy

The paper ”Regulation of Data-driven Market Power in the Digital Economy” (Fast, V., Schnurr, D., Wohlfarth, M.) will be presented at the 11th FSR Annual Conference “From Data Spaces to Data Governance” (9-10 June, 2022).

Abstract:

Digital technology creates a wealth of data and has therefore given rise to a new economy. Data itself is now recognized as a resource which creates business value for firms. The European Commission, for example, has vowed to build the European Data Economy, acknowledging that “access to data spurs marketplace efficiency and innovation” (European Commission, 2016, p. 10). At the same time, the internet economy has born a small number of superstar firms, whose success is frequently attributed to their superior access to data. However, whether the business value created by these firms yields long-term economic benefits for all stakeholders is controversially debated.

Recent high-profile antitrust cases have put a spotlight on the relationship between firms’ access to big data and sustained competitive advantages in digital markets. In Europe, concerns about data-driven market power have led policy makers to propose far-reaching regulations of information technology (IT). Despite the global policy relevance and the potential impact of new data regulation, research
at the intersection of regulatory design of IT artifacts, economic implications as well as legal aspects is scarce.

Therefore, in this study, we develop an overarching research framework that captures the major issues and dimensions of the regulation of data-driven market power which can serve as a basis for future interdisciplinary research on the regulation of IT as well as policy initiatives in this domain. To this end, we investigate three main research questions: (i) What is the empirical evidence for business value creation from big data? (ii) Which factors facilitate market power based on a sustained competitive advantage from data-driven business value creation and could thus warrant regulation? (iii) Which regulatory approaches and rules are available to regulators to remedy data-driven market power and which role does IT play in the design and implementation of such regulation?

Research Design and Expected Results:

First, we review the academic literature for empirical evidence on business value creation from big (user) data in the internet economy. Based on this integrated empirical evidence, we demonstrate that the collection and use of big (user) data creates significant and manifold business value. However, the literature also identifies moderating factors and diverse value categories that paint a more  nuanced picture. This evidence should be considered by policymakers when assessing the impact of regulatory interventions in digital markets.

Second, we draw on the resource-based view of the firm to investigate under which conditions data-driven business value creation is likely to establish sustained competitive advantages. We propose six facilitating factors that prevent market entrants and competitors from imitating a firm’s data resources and associated business value. In particular, we suggest that (i) exclusive access to data, (ii) exploitative access to data, (iii) economies of scale in data analytics, (iv) digital services ecosystems and economies of scope, (v) network effects and platform
business models, and (vi) data-induced switching costs facilitate data-driven market power. In contrast to previous studies, we conclude that regulation can be warranted, albeit data being a non-rival good.

Third, we highlight that the facilitating factors can serve as starting points for regulation. We categorize three regulatory approaches to mitigate negative effects of data-driven market power. First, empowering consumers aims to increase data mobility through better information transparency and more user control of personal data. Second, data openness aims to increase the availability of data resources, e.g., through mandated data sharing. Third, limiting data scale aims to constrain data-rich firms in exploiting data-driven economies of scale and scope through data silos or structural separation. For each of these three regulatory approaches, we analyze the role of IT artifacts as institutions that mediate the effect of regulatory rules on actual practice.

PRESENTATION