Due to the many large earthquakes that have occurred in recent years, the role of seismic risk reduction in building resilient cities has become a matter of concern. The serious disaster damage brought by seismic hazards causes the adoption of migration policies such as building control in the preparedness phase. However, the restricted budget of governments resulting from the global state of economic distress generates a prioritization problem. A decision support framework could be helpful for governments to systematically integrate the complex information when implementing disaster risk reduction policies toward sustainable development. The purpose of this study was to construct an analytical framework based on Geographic Information System (GIS) and Data Envelopment Analysis (DEA) for addressing the prioritization problem by calculating policy efficiency. The spatial DEA-based framework combines indices calculation, spatial database construction, and DEA. Taiwan is an island located in the Circum-Pacific Belt, and has paid long-term attention to adopting policies for earthquake disaster prevention. A policy of earthquake-oriented urban renewal combining enhanced building capacity and city resilience has recently been implemented. A case study of the Yongkang district of the Tainan Metropolis in Taiwan was conducted in this study. The results show an operable framework and propose a suggestion for planning efficient policy priorities in each decision-making unit. In sum, the analytical framework proposed in this study could be a component of a decision support system for governments to adopt disaster risk reduction policies in the process of policy-making and implementation.

Mitigation policy is regarded as an effective strategy to achieve the purpose of building health resilience and reducing disaster risk with the current high frequency of environmental event occurrences. To enhance public acceptance of mitigation policy, the issue of decision-making behavior has been a concern of researchers and planners. In the past literature, qualitative measures employed to reveal the behavioral intention of hazard risk mitigation cause restricted outcomes due to the problem of sample representativeness and the fact that quantitative research is restricted to discuss the linear relationship between the two selected variables. The purpose of this article is to attempt to construct a Mitigation Policy Acceptance Model (MPAM) to analyze the behavioral intention of seismic risk mitigation strategies. Based on Dual Processing Theory, affective is conducted as the core variable for constructing two types of thinking processes, and the variables of risk perception, trust and responsibility are selected in MPAM from theories and past research. In this study, the mitigation policy of residential seismic strengthening, adapted in Yongkang District of Tainan, has been conducted as the case study. According to the results, the result of model fit test has confirmed the MPAM framework, and two thinking modes could be associated together when people face a risky decision-making process. The variable of affective is the most effective factor to influence each variable, and a direct effect on intention is also shown in this model. The results could provide suggestions in communication risk strategies for the government.