This paper develops a conceptual framework explaining how algorithmic human resource management (HRM) reshapes workplace control, authority, legitimacy and worker resistance. It examines how data-driven surveillance and automated decision-making affect worker autonomy, front-line managerial authority, informational asymmetry, psychological contracts and collective labour relations. The paper argues that harmful outcomes are not inherent to algorithmic management but are more likely under configurations characterised by intensive surveillance, opaque decision rules, limited human oversight, restricted worker voice and weak opportunities for contestation.
The study uses a structured narrative synthesis and conceptual theory-building approach. It integrates labour process theory, Foucauldian surveillance, organisational justice, psychological contract, socio-technical systems and algorithmic-management scholarship. The synthesis develops six propositions that specify the mechanisms through which algorithmic HRM reconfigures organisational control and the conditions under which legitimacy deteriorates and worker resistance emerges. The paper focuses on theoretical integration rather than original empirical data collection or a systematic review protocol.
The analysis indicates that algorithmic HRM can compress worker autonomy, transfer decision rights from front-line supervisors to remote technical actors and consolidate organisational power through informational asymmetries. Opacity can generate perceived bias, erode organisational trust, and encourage demands for explanation and appeal rights. Algorithmic substitution for human management may weaken the relational psychological contract, while surveillance and individualised control can disrupt conventional collective organising and stimulate new technical, legal and data-centred forms of resistance. These outcomes are contingent on system design, governance arrangements, worker voice and meaningful human oversight.
This paper offers original value by reframing algorithmic HRM as a data-driven and surveillance-based regime of organisational control rather than a neutral technological innovation. It advances HRM theory by integrating labour process theory, organisational justice and socio-technical systems to explain how informational asymmetries and legitimacy perceptions link algorithmic authority to worker responses and resistance. The study provides a coherent framework for understanding how data-driven HRM reshapes power, autonomy and contestation and offers novel insights for HRM scholarship, practice and governance debates on algorithmic management.
