Algorithmic HRM Systems and Precarious Work Outcomes in Bangladesh’s Gig Economy

This thesis investigates the impact of platform-based algorithmic human resource management (HRM) systems on the working conditions of gig economy workers in Bangladesh. Focusing on platforms such as Pathao, Uber, Foodpanda, and Foodie, the study examines how algorithmic task assignment, compensation structures, and performance evaluations affect worker autonomy, job satisfaction, stress, and overall work quality. The research highlights the interplay between technology-driven management and precarious labor conditions, offering insights for policymakers and platform operators seeking to improve the rights, well-being, and working conditions of gig workers.

• Supervision