Paper Number
ECIS2026-1138
Paper Type
CRP
Abstract
Fairness in healthcare shift scheduling is crucial for well-being of workers but remains challenging to achieve due to numerous requirements. While electronic rostering (e-rostering) helps manage the complexity of shift scheduling, its impact on fairness remains unclear. First, we develop a stimulus-organism-response model guided by organizational justice theory to explain how contextual factors in healthcare shift scheduling (schedule predictability, scheduling control, and relationship with supervisors) shape workers’ scheduling fairness perceptions and, in turn, influence job satisfaction. Second, we examine how e-rostering, compared to human scheduling, alters the relationships in this model. Using data from 185 healthcare workers, our results show that contextual factors significantly impact fairness perceptions, and salience shifts from procedural to distributive fairness in determining job satisfaction under e-rostering. We contribute to future research by highlighting how technologies can reshape the relationship between fairness and work attitudes, and to practice by offering design guidance for fair e-rostering.
Recommended Citation
Bieri, Manuel; Matt, Christian; Bersier, Maude; and Baumann, Philipp, "Fairness In Healthcare E-Rostering: An Empirical Analysis Of Antecedents and Effects" (2026). ECIS 2026 Proceedings. 1.
https://aisel.aisnet.org/ecis2026/hit/hit/1
Fairness In Healthcare E-Rostering: An Empirical Analysis Of Antecedents and Effects
Fairness in healthcare shift scheduling is crucial for well-being of workers but remains challenging to achieve due to numerous requirements. While electronic rostering (e-rostering) helps manage the complexity of shift scheduling, its impact on fairness remains unclear. First, we develop a stimulus-organism-response model guided by organizational justice theory to explain how contextual factors in healthcare shift scheduling (schedule predictability, scheduling control, and relationship with supervisors) shape workers’ scheduling fairness perceptions and, in turn, influence job satisfaction. Second, we examine how e-rostering, compared to human scheduling, alters the relationships in this model. Using data from 185 healthcare workers, our results show that contextual factors significantly impact fairness perceptions, and salience shifts from procedural to distributive fairness in determining job satisfaction under e-rostering. We contribute to future research by highlighting how technologies can reshape the relationship between fairness and work attitudes, and to practice by offering design guidance for fair e-rostering.
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