Understanding Algorithmic Management in the Traditional Work Context: A Quantitative Analysis

Amelie Lena Schmid () and Manuel Wiesche ()
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Amelie Lena Schmid: TU Dortmund University
Manuel Wiesche: Robert Bosch GmbH

A chapter in Digital Innovation and Organizational Transformation, 2026, pp 299-325 from Springer

Abstract: Abstract Algorithmic management (AM) is increasingly transferred to the traditional work context (TWC) and is applied to support the management of permanent workers. AM only partially replaces human managers here, but the core elements of AM remain similar. Hence, AM is implemented into pre-existing organizational structures to enhance processes and performance. While AM in the platform-based context is already well-researched, its implications for the TWC from a managerial perspective remain unclear. To enhance our understanding, we conduct a quantitative study analyzing the utilization of AM at an international automotive supplier. Using linear mixed modeling, we examine a data set of 12,743 error records and reveal that AM has performance advantages in the TWC as it reduces the error resolving time of workers. Furthermore, the impact of influencing factors such as workforce involvement, task complexity, time of work, and experience with AM are considered, evaluated, and discussed.

Keywords: Algorithmic management; Traditional work context; Manufacuturing data (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-032-08483-5_20

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DOI: 10.1007/978-3-032-08483-5_20

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