A sequential group decision process for emergency response

Emergency Decision Making (EDM) in crisis management has some specific features distinguishing itself from traditional decision-making, for example, uncertain information and evolving over time. This paper studies such features and proposes a method based on sequential group decision process. A procedure of group decision-making in emergency response consists of several stages. Each stage finishes a round of group decision-making for a specific emergent scenario, and implements specific actions. The emergency will then respond to the actions, thus the current emergency will evolve into a new emergency and the next round of a group decision-making begins. The continuation of such a procedure forms a sequential group decision process. Layered on such a sequential group decision process, a Group Decision-making Support System (GSS) adopts Case Based Reasoning (CBR) to retrieve similar cases from Case Base and applies Bayesian Dynamic Forecasting Model to forecast the prior distribution of absent feature values. The retrieved results are then put into hidden patter discovery and meta-synthesis of preference adjustment in group decision-making to order suggested solutions and assist consensus achieving among decision makers. The proposed method is suitable to emergency decision making as it supports uncertainty and evolutionary characters of emergency response.