JOURNAL ARTICLE
Active Choice vs. Inertia? An Exploratory Assessment of the European Microsoft Case's Choice Screen.
Published In: Journal of Competition Law & Economics, 2023, v. 19, n. 1. P. 60 1 of 3
Database: Legal Source 2 of 3
Authored By: Duque, Omar Vasquez 3 of 3
Abstract
The article examines the impact of the browser "choice screen" remedy resulting from the 2009 European Commission settlement with Microsoft, which required Windows users in the European Economic Area (EEA), Croatia, and Switzerland to be presented with a screen allowing them to select their preferred web browser instead of defaulting to Internet Explorer (IE). Using StatCounter data and a Differences-in-Differences empirical approach comparing the EEA to similar developed countries without the choice screen, the analysis finds that the choice screen had a negligible effect on reducing IE's market share—estimated between 1.4 and 2 percent—despite IE's overall decline coinciding with the remedy's implementation. The study highlights that IE's market share decline was largely driven by the rise of competitors like Chrome and suggests that consumer inertia, familiarity with experience goods, and the design and reach of choice screens influence their effectiveness. It concludes that policymakers should critically reassess assumptions about default effects and the efficacy of forced choice remedies in digital markets, considering behavioral factors and the heterogeneity of consumer preferences.
Additional Information
- Source:Journal of Competition Law & Economics. 2023/03, Vol. 19, Issue 1, p60
- Document Type:Article
- Subject Area:Law
- Publication Date:2023
- ISSN:17446414
- DOI:10.1093/joclec/nhac009
- Accession Number:162393785
- Copyright Statement:Copyright of Journal of Competition Law & Economics is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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