Digital labour platforms (DLPs) digitally connect human workers with consumers, for a type of work known as digital platform work. DLPs face challenges due to the complexity of control of digital platform work: controlling a large number of workers, high flexibility of work, and aggravated worker resistance. Accordingly, they execute control through algorithmic, which, however, presents problematic scenarios, such as lack of autonomy and fairness, and low worker well-being. Problematizing control executed solely through algorithms, we address the research question: How are workers in digital platform work controlled by algorithmic and human controllers? Based on a study of digital platform work in one of the world's largest app-based food delivery DLPs, we develop the concept of control partitioning, theorizing the distribution of the control of digital platform work between multiple controllers (i.e., DLPs, third-party intermediaries, and customers) and between algorithmic and human control mechanisms. Control partitioning provides a novel theoretical perspective that brings the human back into the loop of control, in contrast to existing studies which suggest DLPs as the only controllers and algorithmic control as the exclusive control means.
