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    Algorithms as work designers: How algorithmic management influences the design of jobs

    Access Status
    Fulltext not available
    Embargo Lift Date
    2024-05-11
    Authors
    Parent-Rocheleau, X.
    Parker, Sharon
    Date
    2021
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Parent-Rocheleau, X. and Parker, S.K. 2021. Algorithms as work designers: How algorithmic management influences the design of jobs. Human Resource Management Review. Article No. 100838.
    Source Title
    Human Resource Management Review
    DOI
    10.1016/j.hrmr.2021.100838
    ISSN
    1053-4822
    Faculty
    Faculty of Business and Law
    School
    Future of Work Institute
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/FL160100033
    URI
    http://hdl.handle.net/20.500.11937/85246
    Collection
    • Curtin Research Publications
    Abstract

    We review the literature on algorithmic management (AM) to bridge the gap between this emerging research area and the well-established theory and research on work design. First, we identify six management functions that algorithms are currently able to perform: monitoring, goal setting, performance management, scheduling, compensation, and job termination. Second, we show how each AM function affects key job resources (e.g., job autonomy, job complexity) and key job demands (e.g., workload, physical demands); with each of these resources and demands being important drivers of worker motivation and their well-being. Third, rejecting a deterministic perspective and drawing on sociotechnical systems theory, we outline key categories of variables that moderate the link between AM on work design, namely transparency, fairness and human influence (e.g., whether workers can control the system). We summarize our review in the form of a model to help guide research on AM, and to support practitioners and designers in the creation and maintenance of meaningful jobs in the era of algorithms.

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