|dc.description.abstract||This dissertation presents extended frameworks of strategic analysis for natural disaster risk control. Natural disasters have properties of low frequency and severe loss, especially catastrophic flood and earthquake. For government or a private company, there are several kinds of actions for flood and earthquake risk control, i.e. structure retrofitting, insurance policy purchasing, catastrophe bond issuing, emergency planning and subsidiary reserve (for workers compensation and etc.). The direct and indirect economic losses caused by the simulated disasters can be estimated using the engineering and financial analysis model. Basing on the model, we can calculate how much loss will be ceased or transferred to other entities, if some budgets spent on risk control actions.
In addition, from various points of view, I try to define the optimal strategy and evaluate it. There are two bundles of models proposed: deterministic analysis models and stochastic analysis models. Deterministic analysis models include two kinds of concepts: interpretive structural modeling (ISM) and economic utility constrained-maximization. Stochastic models start with EP (Exceeding probability) curve into various fascinating optimal models. The background and purpose of this study are to establish a strategy to determine the risk control plan in which consideration is given to the balance with the economic effects (e.g. decrease in damage cost) due to disaster prevention. ISM developed acts as a tool for top management to understand the variables of natural disaster risk control. Though ISM is developed on the basis of perception of the experts of natural disaster risks, the results are quite generic and helpful for the top management to drive the efforts towards the roots of the problem. Furthermore, in economic utility constrained-maximization and stochastic models, these values were compared between those risk control actions to determine the priority and provide data to help evaluate the profitability of each risk control action.
Several aspects of risk and uncertainty are discussed within the context of economic utility constrained-maximization models with a major focus on the importance of risk and uncertainty in research evaluation, how strategy determines insurance and risk control plans, and a real-world example dealing with risk and uncertainty. The core of a default risk-based probabilistic decision model is the development of an ＂exceeding probability curve＂ that synthesizes stochastic dominance test results to rank the ordering of risk control and accounts for different decision makers’’ biases with respect to risk. Some further analyses are described that complement stochastic dominance in significant ways.