Blinded by “algo economicus”: Reflecting on the assumptions of algorithmic management research to move forward
Laura Lamers, Jeroen Meijerink, Giorgio Rettagliata
Human Resource Management · 2024 · Volume 63 · Issue 3
Abstract
This paper reflects on the paradigmatic assumptions and ideologies that have shaped algorithmic management research. We identify two sets of assumptions: one about the “ontology of algorithms” (which holds that human resource management [HRM] algorithms are non-human entities with material agency) and one about the “ontology of management” that HRM algorithms afford (which understands algorithmic management as a form of control for maximizing economic/shareholder value). We explain how these core assumptions underpin existing research of HRM algorithms, causing blind spots that hinder new ways of understanding and studying algorithmic management. After identifying and unpacking the assumptions and blind spots, we offer avenues to overcome these blind spots, allowing for future research based on new ideological assumption grounds that will help move algorithmic management scholarship further in significant ways.
Keywords
agency, algorithmic management, assumptions, HRM algorithms, ontology, reflection
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