ABSTRACT Industry 4.0 is forcing thxike Ergonomics and Human Factors (E&HF) discipline to evolve. E&HF researchers and practitioners must now grapple with features of complexity, such as dynamism, systemic emergence, and scale—features the conventional Human Reliability Assessment (HRA) toolkit is not well adapted to. This paper shows how the capability of HRA can be significantly enhanced to directly confront the long‐standing challenge of identifying and measuring emergence in work systems. The NEXUS framework is introduced as a proof of concept that integrates three established approaches, agent‐based modeling, DynEAST, and HRA, and applies them to a live rail maintenance case study. By embedding human error probabilities (HEPs) into a stochastic ensemble of DynEAST network simulations, NEXUS captures the divergence between deterministic baseline performance and the distribution of outcomes arising from human performance variability, providing a formal, measurable index of emergence. Comparing ensembles parameterized with observed and intervention HEPs then yields a principled basis for evaluating how effectively targeted interventions attenuate emergent variance at the system level. The findings demonstrate that NEXUS can capture meaningful emergent aspects of work system performance and test the relative impact of proposed interventions, expanding the analytical boundaries of HRA toward methods compatible with the systems thinking paradigm that now predominates in E&HF.
Holman et al. (Wed,) studied this question.