Paper Type
Complete
Abstract
Fairness in shift scheduling is essential for workers because it substantially affects their well-being and private lives. Since creating fair shift schedules is difficult due to numerous constraints, algorithmic support is increasingly used. However, the perceptional basis for fairness from the workers’ perspective is still missing for optimizing algorithmic shift scheduling systems. Drawing from organizational justice theory (OJT), we conducted 19 semi-structured interviews with healthcare workers from three Swiss hospitals. The iterative thematic analysis refines established fairness dimensions and provides a comprehensive, context-specific, multi-level understanding of how healthcare workers perceive fairness in their organizational and operational framework. We extend the literature by providing application-specific norms and important determinants of fair shift scheduling procedures in healthcare facilities, which can be the basis for fair algorithmic scheduling systems and support healthcare facilities and software developers to evaluate and optimize their current shift scheduling approaches.
Paper Number
1274
Recommended Citation
Bieri, Manuel and Matt, Christian, "Algorithmic Fairness in Shift Scheduling – Assessing the Fairness Perceptions of Healthcare Workers" (2025). AMCIS 2025 Proceedings. 17.
https://aisel.aisnet.org/amcis2025/intelfuture/intelfuture/17
Algorithmic Fairness in Shift Scheduling – Assessing the Fairness Perceptions of Healthcare Workers
Fairness in shift scheduling is essential for workers because it substantially affects their well-being and private lives. Since creating fair shift schedules is difficult due to numerous constraints, algorithmic support is increasingly used. However, the perceptional basis for fairness from the workers’ perspective is still missing for optimizing algorithmic shift scheduling systems. Drawing from organizational justice theory (OJT), we conducted 19 semi-structured interviews with healthcare workers from three Swiss hospitals. The iterative thematic analysis refines established fairness dimensions and provides a comprehensive, context-specific, multi-level understanding of how healthcare workers perceive fairness in their organizational and operational framework. We extend the literature by providing application-specific norms and important determinants of fair shift scheduling procedures in healthcare facilities, which can be the basis for fair algorithmic scheduling systems and support healthcare facilities and software developers to evaluate and optimize their current shift scheduling approaches.
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