Obfuscation and Shrouding with Network Effects: Big Data Strategies and the Limits of Competition
32 Pages Posted: 24 Aug 2017 Last revised: 20 Jul 2018
Date Written: August 21, 2017
This article analyses Big Data strategies with network effects. An incumbent network can abuse its market dominance by implementing a Big Data strategy that “shrouds” data collection. Thereby, only “sophisticated” consumers understand that data collection yields a dis-utility while “naive” consumers do not. Shrouding only emerges after both, sophisticates and naives joined the incumbent network in the first place. This guarantees that naives become locked-in. Subsequent market entry by a network that does not collect data fails, as the naives’ inertia keeps sophisticates, too, from switching. Surprisingly, multihoming exacerbates data collection showing that competition cannot prevent abusive Big Data strategies.
Keywords: Big Data, Antitrust, Consumer Protection, Excess Inertia, Bounded Rationality
JEL Classification: K21, L12, D41
Suggested Citation: Suggested Citation