Does data portability facilitate entry?

Abstract

Data portability rules are generally thought to encourage consumers to switch between different service providers and facilitate entry of new firms. Some of these rules, however, only apply to data “provided by” the consumer (data subject), e.g., purchasing patterns. Data “derived by” a firm (data controller) with the help of data analytics, e.g., recommendations derived from purchasing patterns, does not fall under data portability rules. We show that, under the current legislation along with extensive use of data analytics, data portability may hinder switching and entry due to the demand-expansion effect: the prospect of easier switching due to data portability may entice consumers to provide even more data to the incumbent, which strengthens the incumbency advantage. Hence, the effectiveness of data portability in fostering competition will depend on what types of data are portable. More generally, in analysing the effectiveness of polices aiming at reducing ex post switching costs, it is important to take into account their impacts on ex ante actions that build up endogenous entry barrier.

Publication DOI: https://doi.org/10.1016/j.ijindorg.2019.102564
Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
College of Business and Social Sciences > Aston Business School
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Data portability,Entry barrier,GDPR,Industrial relations,Aerospace Engineering,Economics and Econometrics,Economics, Econometrics and Finance (miscellaneous),Strategy and Management,Industrial and Manufacturing Engineering
Publication ISSN: 0167-7187
Last Modified: 01 Nov 2024 08:12
Date Deposited: 13 Jan 2020 14:50
Full Text Link:
Related URLs: https://linking ... 16771871930092X (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2020-03-01
Published Online Date: 2019-12-13
Accepted Date: 2019-12-09
Authors: Lam, Wing Man Wynne
Liu, Xingyi (ORCID Profile 0000-0003-3816-4126)

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