How Big Data Confers Market Power to Big Tech: Leveraging the Perspective of Data Science

• Published in: Antitrust bulletin Vol. 65; no. 3; pp. 459 - 485
• Main Authors: Santesteban, Cristian, Longpre, Shayne
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-09-2020; Sage Publications, Inc
• Subjects: Analysis; Antitrust law; Barriers to entry (Industrial organization); Big data; Computer services industry; Ethical aspects; Influence; Information management; Interpretation and construction; Laws, regulations and rules; Management; Market power; Prevention; Remedies; online platforms; data science; barriers to entry; Big Data; digital economy; market power; machine learning; artificial intelligence; Big Tech
• ISSN: 0003-603X; 1930-7969
• DOI: 10.1177/0003603X20934212

Data-hungry applications are central to the largest online platforms. Using a novel approach that leverages data science to inform the economics, we demonstrate how data is a source of market power. We highlight the importance of data heterogeneity, whereby small feature differences translate into large value differences. We examine how concept drift, the existence of a nonstationary relationship between the predictive and target variables, implies that access to a continuous stream of data is competitively advantageous. We analyze how an information bottleneck and high sample complexity in existing applications lead to increasing returns to data. Finally, we show how user interaction control enables personalization that raises switching costs. The combined effect is a potent data barrier to entry that endows substantial market power to only the largest online platforms. Competition policy should focus on enabling entrants unfettered access to vast continuous data streams similar to those available to platform incumbents.