Transparency of Algorithmic Control Systems and Worker Judgments

Maximilian Kempf (), Filip Simić (), Armin Alizadeh () and Alexander Benlian ()
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Maximilian Kempf: Technical University of Darmstadt
Filip Simić: Technical University of Darmstadt
Armin Alizadeh: Technical University of Darmstadt, Information Systems and Electronic Services
Alexander Benlian: Technical University of Darmstadt, Information Systems and Electronic Services

A chapter in Digital Innovation and Organizational Transformation, 2026, pp 263-279 from Springer

Abstract: Abstract The use of algorithms to guide worker behavior, referred to as algorithmic control (AC), is increasingly prevalent in organizations. Despite its potential operational benefits, prior research indicates that workers often struggle with the opaque nature of such systems. Our research aims to explore how workers perceive, judge, and react to AC systems when exposed to two distinct facets of algorithmic transparency (AT): input and transformation AT. Through an experimental study with 121 participants, we provide empirical evidence that increased transparency about the algorithm’s transformation process significantly enhances workers’ perceived AT, which in turn positively impacts workers’ judgments and, ultimately, their continuance intention and acceptance of an AC system. In doing so, we provide practical recommendations for organizations to mitigate the adverse effects associated with algorithmic control.

Keywords: Algorithmic control; Algorithmic transparency; Worker judgments (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_18

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DOI: 10.1007/978-3-032-08483-5_18

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