방법 비교

	Household Disaster Preparedness Scale	Evacuation Time Estimation Modeling
분야	Disaster Studies	Disaster Studies
계열	Latent structure	Process / pipeline
기원 연도	2000	2008
창시자	Michael K. Lindell & David J. Whitney	Michael K. Lindell (EMBLEM2); regional evacuation modeling tradition
유형	Multi-item measurement scale of household preparedness behavior	Behavioral-and-network model of mass evacuation duration
원전	Lindell, M. K., & Whitney, D. J. (2000). Correlates of Household Seismic Hazard Adjustment Adoption. Risk Analysis, 20(1), 13-26.	Lindell, M. K. (2008). EMBLEM2: An empirically based large scale evacuation time estimate model. Transportation Research Part A: Policy and Practice, 42(1), 140-154.
별칭	Disaster Preparedness Scale, Household Hazard Adjustment Scale, Preparedness Behavior Index	Evacuation Time Estimate Modeling, ETE Modeling, Mass Evacuation Modeling
관련	3	3
요약	A household disaster preparedness scale measures the extent to which households have adopted actions that reduce their vulnerability to hazards — what the disaster literature calls hazard adjustments. Grounded in Michael Lindell and David Whitney's work on the correlates of seismic hazard adjustment adoption and connected to the broader Protective Action Decision Model, the scale assembles a set of concrete preparedness items — structural measures, survival supplies, and planning actions — and scores how many a household has taken. Beyond producing a preparedness index, the method models what predicts adoption, and a central, robust finding is that households' perceptions of the attributes of each adjustment (its efficacy, cost, time, and difficulty) predict adoption more strongly than fear or risk perception alone. The scale thus serves both to quantify preparedness and to explain why some households prepare while others do not.	Evacuation time estimate (ETE) modeling predicts how long it will take to move an at-risk population to safety, a quantity central to emergency planning for hurricanes, floods, wildfires, nuclear plants, and other hazards. The method joins two ingredients: a behavioral component describing when households decide to leave — the mobilization or 'loading' curve, grounded in warning-response research such as the Protective Action Decision Model — and a transportation component describing how fast the road network can carry them away. Michael Lindell's EMBLEM2 exemplifies the empirically based approach, letting emergency managers compute ETEs from a modest set of route, behavioral, and scope parameters and even update them in real time as a hazard approaches. By combining human departure timing with network capacity, ETE modeling tells planners when to issue evacuation orders and where congestion will bind, turning evacuation from guesswork into quantified logistics.