The Applied Economics Office (AEO) at NIST works closely with the NIST Community Resilience Program (CRP) and external collaborators to pursue a science-based approach to resilience planning. Resilience and reliability are emerging focus areas in the design of the built environment with the aim of improving preparedness and recovery from disruptive events. More research is needed to understand the planning, protective, and recovery processes of its highly interdependent physical, social, and economic systems. In particular, advancements in measurement science are needed to estimate the economic impact from planned community resilience enhancements that address hazards (e.g., natural hazards, human-made hazards, and other unexpected hazardous shocks and stressors).
This research effort relies extensively on modeling and optimization, with consideration for field data collection, and statistical and geospatial data analysis. Informed by the combined research of the AEO and the CRP, web-accessible tools are being developed (e.g., the Economic Decision Guide Software – EDGe$ Online Tool) to support community resilience planning. Therefore, strong computer skills, including computer programming, are valued. Continued research is focused upon the emergence of complex event decision-making when there are concurrent and/or cascading risks involved. This research space seeks to identify resilience strategies that achieve other community goals (e.g., economic development, safety, and equity) through co-benefits, some of which may not have a straight-forward market value.
Multiple disciplines will be considered, including engineering (e.g., civil, industrial, operations research, computer science), economics (applied, micro, macro), social sciences (e.g., sociology, planning, decision science), and public health science (e.g., disaster epidemiology, biostatistics).
Agent-based Modeling; Applied Economics; Benefit-Cost Analysis; Buildings; Community Resilience; Decision Making; Engineering; Infrastructure systems; Social systems; Metrics; Systems modeling; Social Science; Operations research; Mathematical programming; Optimization; Systems analysis; Risk analysis; Industrial Engineering; Sociology; Planning; Decision Science; Public Health; Disaster epidemiology; Statistics