From Managers to Machines: How Algorithmic Goal Setting Affects Intrinsic Motivation at Work
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2025-06-27
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en
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This thesis explores the relationship between algorithmic goal-setting (AGS) and employees’ intrinsic motivation, focusing on the moderating role of transparency and the psychological needs of autonomy, competence and relatedness as outlined in Self-Determination Theory. Algorithmic management, which uses data-driven algorithms to automate core managerial functions, is increasingly prevalent beyond gig platforms and is now being implemented across a wide range of traditional workplaces. Despite this trend, there is limited empirical research on how such systems affect employees’ motivation. While AGS promises efficiency, it may also undermine employees’ psychological needs. The degree of transparency with which AGS is implemented is often proposed as a way to counteract these risks, as it may potentially buffer the dehumanizing effects of algorithmic systems. This study therefore investigates how transparency moderates the relationship between AGS and intrinsic motivation.
To empirically assess these dynamics, this study employs a quantitative 2x2 between-subjects vignette-based experimental design in which 122 participants were asked to imagine themselves as blue-collar workers in a bicycle factory. Each participant was randomly assigned to one of four scenarios that varied in goal-setting source (whether goals were set by a human manager or an algorithm) and in transparency (whether or not an explanation for the assigned goals was provided). The data were analyzed using both simple mediation and moderated mediation analyses.
Results suggest that AGS is associated with lower competence and, to a lesser extent, relatedness satisfaction under transparent conditions, which in turn relate to reduced intrinsic motivation. Contrary to expectations, transparency did not buffer these associations but seemed to make them more salient. No significant associations were found for autonomy. These findings challenge the universally positive view of transparency and highlight its context-dependent role. The study contributes to a more nuanced understanding of AGS and supports human-centered implementation in line with Industry 5.0 principles.
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Faculteit der Managementwetenschappen