A comparative study of algorithmic management and control mechanisms. A platform-centric review, comparing food delivery platforms in the UK and Sweden
(2025) MGTN59 20251Department of Business Administration
- Abstract
- This thesis conducts a comparative analysis of algorithmic management in the food delivery platform sector, focusing on platforms operating in the United Kingdom and Sweden. Drawing upon Institutional Theory, Labour Process Theory and Discourse Analysis, the study investigates how platforms such as Uber Eats, Deliveroo, Foodora and Wolt implement, regulate and communicate algorithmic control in distinct institutional environments. By analysing corporate communications, legal frameworks, union documents and media source, the research identifies key similarities in the technological use of algorithmic management, particularly in task allocation and performance monitoring. However, significant differences emerge in employment models,... (More)
- This thesis conducts a comparative analysis of algorithmic management in the food delivery platform sector, focusing on platforms operating in the United Kingdom and Sweden. Drawing upon Institutional Theory, Labour Process Theory and Discourse Analysis, the study investigates how platforms such as Uber Eats, Deliveroo, Foodora and Wolt implement, regulate and communicate algorithmic control in distinct institutional environments. By analysing corporate communications, legal frameworks, union documents and media source, the research identifies key similarities in the technological use of algorithmic management, particularly in task allocation and performance monitoring. However, significant differences emerge in employment models, regulations and contestation shaped by national labour regimes. Sweden’s coordinate market economy fosters greater institutional negotiation and worker protections, whilst the UK’s liberal market economy permits more precarious, unregulated platform practices. The findings highlight how platform governance is embedded within broader socio-economic structures and demonstrate that algorithmic management cannot be disentangled from the institutional contexts in which it operates. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9194346
- author
- Challender, Luke LU and Viskum, Theobald LU
- supervisor
- organization
- course
- MGTN59 20251
- year
- 2025
- type
- H1 - Master's Degree (One Year)
- subject
- language
- English
- id
- 9194346
- date added to LUP
- 2025-06-27 14:04:58
- date last changed
- 2025-06-27 14:04:58
@misc{9194346, abstract = {{This thesis conducts a comparative analysis of algorithmic management in the food delivery platform sector, focusing on platforms operating in the United Kingdom and Sweden. Drawing upon Institutional Theory, Labour Process Theory and Discourse Analysis, the study investigates how platforms such as Uber Eats, Deliveroo, Foodora and Wolt implement, regulate and communicate algorithmic control in distinct institutional environments. By analysing corporate communications, legal frameworks, union documents and media source, the research identifies key similarities in the technological use of algorithmic management, particularly in task allocation and performance monitoring. However, significant differences emerge in employment models, regulations and contestation shaped by national labour regimes. Sweden’s coordinate market economy fosters greater institutional negotiation and worker protections, whilst the UK’s liberal market economy permits more precarious, unregulated platform practices. The findings highlight how platform governance is embedded within broader socio-economic structures and demonstrate that algorithmic management cannot be disentangled from the institutional contexts in which it operates.}}, author = {{Challender, Luke and Viskum, Theobald}}, language = {{eng}}, note = {{Student Paper}}, title = {{A comparative study of algorithmic management and control mechanisms. A platform-centric review, comparing food delivery platforms in the UK and Sweden}}, year = {{2025}}, }