Modeling emergency response operations: A theory building survey

•State-of-the-art survey focused on operations research models of unfolding emergencies.•Unsupervised learning techniques used to detect and agnostically name research clusters.•Reveals extant research clustered around distinct response processes such as evacuation.•Dominant axioms portray processes managed in isolation, often with definitive solution.•Greater attention is needed to modeling the passage of time and interaction of processes. During the response phase of an emergency, decision makers manage processes that save lives, protect infrastructure and contain evolving threats. In this paper, we undertake a comprehensive survey of the emergency response operations literature. In collating and classifying our literature sample, we employ novel methodologies adapted from unsupervised learning and network analysis to reduce sampling and expectancy biases. We find that operations research supporting emergency response has been developing in discernible clusters, with each cluster of studies focused on a particular process such as evacuation or aid distribution. Our study both serves to strengthen the theoretical foundation of emergency response operations and identifies plentiful opportunities for researchers seeking to advance the state-of-the-art in this exciting frontier of operations research.