JOURNAL ARTICLE
Fairness and contestability in the provision of software application stores services.
Published In: Journal of Antitrust Enforcement, 2024, v. 12, n. 2. P. 309 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Padilla, Jorge 3 of 3
Abstract
The article discusses the European Commission's decision to fine Apple for abusing its dominant position in the market for music streaming apps on its App Store. The Commission found that Apple's anti-steering provisions prevented app developers from informing users about alternative and cheaper music subscription services. The Commission ordered Apple to remove these provisions and comply with the Digital Markets Act (DMA), which requires Apple to allow app developers to communicate and promote offers in-app, permit third-party app stores, and provide access to the App Store on fair terms. Apple's compliance proposal has been criticized for potentially stifling the development of alternative app stores. The Commission has opened non-compliance investigations to determine if Apple's proposal falls short of its obligations under the DMA. The article explores the relationship between fairness and contestability in the provision of app store services and discusses the need to regulate the division of surplus between gatekeepers and business users. The author suggests that compliance with DMA requirements may not guarantee fairness and that the Commission may need to regulate how surplus is divided to ensure fair treatment of business users. [Extracted from the article]
Additional Information
- Source:Journal of Antitrust Enforcement. 2024/07, Vol. 12, Issue 2, p309
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2024
- ISSN:2050-0688
- DOI:10.1093/jaenfo/jnae032
- Accession Number:178481218
- Copyright Statement:Copyright of Journal of Antitrust Enforcement 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.