Disjunctures in Algorithmic HRM: Tracing Gaps Between Intent, Implementation and Perception in Gig Work

ABSTRACT The rise of gig work, enabled by algorithmic management, has reconfigured the traditional employer‐employee relationship, giving rise to new tensions in how Human Resource Management (HRM) is enacted and experienced. While existing scholarship acknowledges the relevance of HRM in this domain, little is known about how HRM intentions are operationalized through algorithmic management in gig work and how these efforts are perceived by gig workers. Therefore, using a case study approach, we aim to examine the disjuncture emerging of HRM implementation across intended, actual and perceived levels within gig work. Our findings demonstrate that these disjunctures' arise as structural outcomes of socio‐technical systems that mediate implementation. Building on this insight, the study makes three contributions. First, it advances the performance–control debate by demonstrating how algorithmic management redistributes and reconstitutes control across HRM levels. Second, it extends the rhetoric–reality debate by showing how algorithmic systems selectively translate and reshape HR rhetoric in practice. Third, it contributes to the literature on contemporary forms of bureaucratic control by illustrating how algorithmic infrastructures reconfigure the locus of HRM, embedding coordination and evaluation within platform architectures and situating HRM within pre‐structured systems of control.