Background:  Despite the utilization of algorithms as data management tools, they are increasingly used as people management tools to allocate, optimize and evaluate workers. This is especially popular among digital labor platforms of the gig economy as it is seen as one of the core innovations that enabled such platforms. Usually, these platform workers are self-employed, which results in an apparent autonomy while working under a rigid algorithm. For those workers, proactively shaping the job according to their own needs and abilities, commonly known as job crafting, may be increasingly important. As research suggests that job crafting occurs across professions and industries, how is it possible under the constraints of algorithmic management?  Purpose:  This thesis investigates the abilities of German food delivery riders of the company Lieferando to perform job crafting while being managed by an algorithm.  Method:  To meet the purpose of this study, the authors conducted a qualitative study. The data was collected through technology-mediated interviews with riders of the company Lieferando in Germany. The authors applied an online recruitment strategy through various social media websites to find suitable interviewees. Interview partners were picked with a random sampling strategy. The interviews were semi-structured, and the researchers guided the interviewees through a previously prepared topic guide with open-ended questions.  Conclusion:  The results of this study provide empirical evidence that riders of the food delivery company Lieferando engage in job crafting activities although working under the constraints of algorithmic management. The outcomes further show that all riders performed task crafting and cognitive crafting in various ways, whereas engagement in relational crafting was less developed. Riders not only have the ability to modify their work but also enrich it.  The findings of this study allow to draw several theoretical and managerial implications as well as provide possible research opportunities for future studies.

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.

Cette thèse porte sur le cas de l’organisation Uber Technologies à Montréal afin de discuter de l’essor fulgurant des plateformes numériques dans la foulée de la crise des subprimes en 2008. Elle expose l’écosystème des plateformes numériques tout en s’interrogeant sur les vecteurs d’expansion de l’organisation Uber en tant qu’un archétype des « plateformes allégées » (Srnicek, 2016) exploitant l’accès aux capitaux de risque, la technologie de pointe, la disruption des régulations en vigueur, dont celle encadrant le travail en reléguant les conducteurs et conductrices au statut de travailleurs et travailleuse autonomes. Les résultats de l’enquête, qui se basent sur un travail ethnographique bonifié par une netnographie et des entrevues semi-dirigées, sont discutés dans trois articles. Dans le premier article, nous abordons, de manière critique, les conditions de travail imposées par Uber dans le contexte plus large de précarisation de l’emploi et de prolifération du travail atypique au Québec (Jamil et Noiseux, 2018) en mettant en relief les ressorts fondant l’exploitation d’une armée de réserve de personnes issues de l’immigration confinées aux marges du marché du travail et de travailleurs pauvres cumulant des emplois afin d’arrondir les fins de mois. Le deuxième article examine en détail le système de surveillance décentralisé encastré dans la gestion algorithmique d’Uber et réactualisant – dans une version autonomisée - le panoptique foucaldien. Le troisième article, adoptant une perspective goffmanienne, interroge les pratiques d’adaptation et de résistances des conducteurs à travers l’analyse de leurs interactions – tant avec les passagers qu’avec l’application Uber - tout au long des différentes étapes du cycle de production d’une course. La thèse se conclut en proposant une conceptualisation du modèle productif découlant de la généralisation des pratiques du lean management dans la production en masses de services désormais standardisées. À cette fin, nous exposons les flux d'information produits par les utilisateurs - conducteurs et passagers – alimentant la gestion algorithmique du processus de la production. Nous y illustrons, le processus d’émiettage des tâches (taskification) encastré dans un processus de production fondé sur l'autonomie contrôlée des chauffeurs Uber et se déployant grâce à la mise en place de « méta-règles » de jeu. Cette analyse critique du système d’accumulation inhérent au modèle organisationnel d’Uber nous amène enfin à proposer une relecture du concept de « nouvelle combinatoire productive » proposé par Durand « 1989) au prisme du développement récent des plateformes allégées et des modèles organisationnels qui les caractérisent. / This thesis examines the case of the Uber Technologies organization in Montreal. We critically analyze the rise of digital platforms in the aftermath of the 2008 subprime crisis. It exposes the ecosystem of digital platforms while questioning the expansion vectors of the Uber organization as an archetype of "lean platforms" (Srnicek, 2016) that thrive on significant access to venture capital, cutting-edge technology, and the disruption of existing regulations, including those that framework by relegating drivers to the status of self-employed workers. Findings based on ethnographic work, complemented by netnography and semi-directed interviews, are discussed in three articles. The first takes a critical stance on the working conditions imposed by Uber in the broader context of the casualization of employment and the proliferation of atypical work in Quebec (Jamil and Noiseux, 2018). It brings to light the dynamics of Uber's exploitation of a reserve army made up of immigrants pushed to the margins of the labor market and a growing number of working poor who take on casual work to make ends meet. The second article examines in detail the decentralized surveillance system embedded in Uber's algorithmic management, updating - in an autonomized version - the Foucauldian panopticon. The third article, adopting a Goffmanian perspective, examines drivers' practices of adaptation and resistance through an analysis of their interactions - both with passengers and with the Uber application - during the various stages of a ride's production cycle. The thesis concludes by proposing a conceptualization of the production model derived from the generalization of lean management practices in the now standardized mass production of services. To this end, we illustrate the information flows produced by users - drivers and passengers - which feed into the algorithmic management of the production process. We also chart the process of taskification embedded in a production process based on the controlled autonomy of Uber drivers and deployed through the implementation of "meta-rules of play". This critical analysis of the accumulation system inherent in Uber's organizational model finally suggests a re-reading of the concept of new combinatoire productive proposed by Durand (1989) in the light of the recent deployment of lean platforms and their organizational models.