Employee Affective Reactions to Algorithmic Management: How Does Context and Algorithm Transparency Matter?

Abstract

The use of algorithmic management (AM) expands continuously, whereas knowledge about the influence of context and algorithm transparency on employee affective reactions to AM is still underdeveloped. To fill these voids, this study draws on the affective response model (Zhang, 2013) and examines the role of different contexts (i.e., work allocation, training allocation, performance evaluation) and levels of algorithm transparency (i.e., high vs. low) for the relationship between the decision-entity (human vs. algorithm) and employee reactions. Results of a vignette study with German employees (N = 354) showed that employees had more positive reactions to AM in training allocation compared to work allocation, whereas both levels of algorithm transparency had similar effects on reactions in the AM condition. Our results shed light into the intricacies of AM reactions, guiding future research directions. Practitioners can leverage these insights to determine contextual nuances of AM and refine consequent communication strategies.