Algorithmic management – the use of advanced algorithms, such as machine learning, to automate coordination and control functions—holds significant potential for modernizing public bureaucracies. Facing increasing demographic pressures and the imperative of digital transformation, public-sector organizations in Germany are actively seeking solutions to streamline processes traditionally managed by human personnel.

This thesis addresses algorithmic management within the German public sector through two primary objectives: first, synthesizing existing academic literature to systematically identify prevalent use cases and practical applications; second, empirically exploring facilitators and barriers influencing the adoption and integration of algorithmic management technologies. Through qualitative interviews with public servants, this research aims to provide nuanced insights into organizational readiness, cultural acceptance, and structural constraints, thus contributing to both theoretical understanding and practical guidance for future implementations.

This thesis can be written in German or English. However, given the international relevance of the topic, we strongly recommend writing it in English. If you are interested, please contact Armin Alizadeh with a short curriculum vitae and current performance record.