JOURNAL ARTICLE
Varieties of platform capitalism? Competition, regime types and the diversity of food delivery platforms across Europe and North America.
Published In: Socio-Economic Review, 2025, v. 23, n. 2. P. 899 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Ametowobla, Dzifa; Kirchner, Stefan 3 of 3
Abstract
This article examines the diversity of platform models in the food delivery sector across 32 countries in Europe and North America, challenging the prevailing notion of a uniform "platform capitalism" model characterized by self-employed labor and monopoly dominance. Using a unique cross-national dataset, the study finds considerable variation in employment relationships—ranging from self-employment to traditional employment and subcontracting—especially across different national institutional regimes. While North American platforms largely conform to the self-employment model, European platforms exhibit significant diversity influenced by competitive dynamics among multinational corporations and distinct regulatory frameworks categorized into regime types such as Anglo-American, Continental, Mediterranean, Nordic, and Eastern European. The findings suggest that platform companies adapt their organizational models in response to local institutional conditions and competition, underscoring the relevance of economic sociology and comparative capitalism theories in understanding the platform economy beyond the limited North American-centric perspective.
Additional Information
- Source:Socio-Economic Review. 2025/04, Vol. 23, Issue 2, p899
- Document Type:Article
- Subject Area:Political Science
- Publication Date:2025
- ISSN:1475-1461
- DOI:10.1093/ser/mwae079
- Accession Number:187125466
- Copyright Statement:Copyright of Socio-Economic Review 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.