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Worker Ant or Your Own Boss? : A Labour Process Analysis of Foodora Riders' Experiences of Algorithmic Management

Introduction: This qualitative case study extends the research of algorithmic management by examining the experiences of food-delivery workers working for the gig company Foodora. As Foodora promotes the job as flexible and autonomous, the utilisation of labour process theory (LPT) in this study helps to uncover if these sentiments hold true in practice by examining what Foodora’s labour process looks like, and how control, autonomy, and individualism take shape in the workplace. Method: Interviews with eight Foodora delivery workers working in Sweden were carried out, where the data was transcribed and coded. Analysis: Using LPT as a framework for the analysis, the material was coded according to the themes of control, transparency, resistance, consent, and individualism. By doing this, the study contextualises algorithmic management within the wider framework of capitalistic management forms and highlights how it impacts worker experiences. Results: The results show that the experiences of the job were largely different among the individual participants of the study. It is proved that Foodora’s employment of algorithmic management impacts almost every aspect of the daily work since it centres around following automated directives which the workers receive through an app. Individualism is accentuated by a self-entrepreneurial discourse promoted by Foodora and the fact that the workforce is dispersed with limited opportunities to interact. Despite being a dispersed workforce, the workers have been able to organise which has led to a growing number of workers joining the union. Conclusion: The impacts of algorithmic management are proved to be evident. The varied experiences of the job could have multiple explanations and needs to be explored further in relation to economical and societal factors. The effects of the newly implemented collective bargaining agreement also need to be examined in future research.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-447237
Date January 2021
CreatorsKarlernäs, Simon
PublisherUppsala universitet, Institutionen för ABM
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationTheses within Digital Humanities ; 7

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