Mitigation Policy Acceptance Model: An Analysis of Individual Decision Making Process toward Residential Seismic Strengthening

Clicks: 207
ID: 79939
2018
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.
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cheng2018mitigationinternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Cheng, Hao-Teng;Tsou, Ko-Wan;
Journal International journal of environmental research and public health
Year 2018
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