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

Georg Clemens

Compass Lexecon

Mutlu Özcan

Ruhr-University Bochum

Date Written: August 21, 2017

Abstract

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

Clemens, Georg and Özcan, Mutlu, Obfuscation and Shrouding with Network Effects: Big Data Strategies and the Limits of Competition (August 21, 2017). Available at SSRN: https://ssrn.com/abstract=3023467 or http://dx.doi.org/10.2139/ssrn.3023467

Georg Clemens

Compass Lexecon ( email )

23 Square de Meeûs
Brussels, 1000
Belgium

Mutlu Özcan (Contact Author)

Ruhr-University Bochum ( email )

Bochum, 44780
Germany

Register to save articles to
your library

Register

Paper statistics

Downloads
165
rank
166,224
Abstract Views
993
PlumX