Abstract
Algorithmic management (AM) as key enabler for managing the workforce in food delivery services has recently raised growing concerns about workers’ occupational well-being (OWB). Existing studies mainly emphasize negative impacts of AM on workers’ OWB, e.g., stress due to constant tracking. Contrastingly, a few studies show positive aspects of AM, e.g., receiving personalized real-time feedback. Getting to the root of these opposing findings, we use the job demands-resources (JD-R) model as theoretical lens to structurally analyze AM-specific job demands (AM-JD) and AM-specific job resources (AM-JR). Based on semi-structured interviews with 21 food delivery riders in Germany, this study paints a nuanced picture of AM, e.g., by identifying AM-JRs, that help to mitigate AM-JDs. We further find that job crafting, i.e., proactively changing work-related boundaries, increases AM-JRs and workers’ OWB. Drawing on our results, we present the integrated DYNAMO Model, which shows the dynamic relationships between AM, OWB, and job crafting.
Recommended Citation
Lippert, Isabell; Kirchner, Kathrin; and Saunders, Carol, "The Dynamic Relationships between Algorithmic Management and Workers' Occupational Well-being: A Job Demands-Resources Perspective" (2023). ECIS 2023 Research Papers. 286.
https://aisel.aisnet.org/ecis2023_rp/286