Determinants of Disaster Mitigation Behaviors in Taiwan
This research investigated determinants of typhoon and earthquake mitigation behaviors in Taiwan based on risk analysis of hazards, exposure, and vulnerability, supplemented by the protective action decision model (PADM). Besides psychological condition (i.e., risk perception, life satisfaction, and anxiety), demographics, and socio-economic characteristics factors (i.e., gender, age, ratio of home ownership, and average monthly income per household) mentioned in the PADM, this research added factors of family structure, social network, and internet and social media usage in the analysis. All of these factors were for the concept of social vulnerability—one dimension of risk analysis. Furthermore, this research used the factor of disaster-prone areas (i.e., disaster experiences, flood-prone areas, and number of protected people possibly affected by debris flow) to represent another dimension of risk analysis: the intersection of hazard and exposure. The 2020 Taiwan Social Change Survey data and multiple hierarchical regression analysis were used for analysis. The results showed that (1) the demographic and socio-economic factor had the greatest impact on mitigation behaviors among all the factors when added hierarchically in the model. This finding added to the literature on the importance of the demographic and socio-economic factor: as the third factor added in the model, it had an impact larger than those of the first and second factors added in the model, namely disaster-prone areas and psychological condition. (2) Risk perception had a larger impact than disaster experience on mitigation behaviors—whether the impact of disaster experience on mitigation behaviors was significant depended on the type of disaster. This result suggested that to encourage mitigation behaviors, actively raising people's risk perception might be a better strategy than passively focusing on disaster experiences. (3) The factor of psychological condition could be an antecedent variable of mitigation behaviors. Experts or practitioners in the field of disaster management could plan how to integrate mental health services into the promotion of disaster mitigation behaviors. (4) Among all variables, education had the greatest impact on mitigation behaviors, which was an exciting result. This result might support the viewpoint of sociology of disasters which believes that education provides capability to absorb knowledge and obtain information of disaster mitigation behaviors. (5) The impact of the factor of family structure on mitigation behaviors was not significant. Unlike the results of previous studies, cohabiting people, especially school-age children, did not encourage family mitigation behaviors in Taiwan. Therefore, the practitioners must continue to work hard to meet their own expectation that school-age children bring home the knowledge they have acquired from school, thereby influencing their families to take disaster mitigation behaviors. The fact that families with access and functional needs did not have more mitigation behaviors than their counterparts suggested a disaster vulnerability in today's aged society. (6) Social networks, the internet, and social media influenced the flood model but were not significant in the earthquake model. As there is still room for improvement, practitioners could learn to effectively use existing social mechanisms to promote and implement disaster mitigation behaviors in Taiwan, such as school-based and neighborhood-based disaster education and management, as well as social media.