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Abstract
This study examined public support for disaster-related measures (risk awareness, memory transmission, prevention facilities, and information networks) in the long-term recovery phase of a disaster-affected municipality. Focusing on Rikuzentakata City, which was severely impacted by the 2011 Great East Japan Earthquake and Tsunami, a stated-preference survey was conducted and analyzed using discrete choice models. Three research questions were addressed: RQ1 on the main effects of disaster-related measures, RQ2 on the interaction effects among these measures, and RQ3 on the interaction effects between disaster-related measures and economic-livelihood measures (ELMs). Stand-alone disaster-related measures and their within-domain combinations reduced public support, indicating dilution effects. By contrast, support increased when they were integrated with complementary ELMs. The policy implications are threefold. First, disaster-related measures should be implemented with caution in the medium- to long-term recovery process, as pursuing them alone may generate dilution effects. Second, integrated policy packages that combine disaster-related measures with complementary ELMs should be prioritized. Third, shrinking-city municipalities can better overcome fiscal and human resource constraints and enhance sustainability by leveraging complementarities across policy domains. Overall, the findings provide quantitative evidence that disaster-related policy must be reconceptualized as part of a broader policy portfolio. This insight has broader relevance for hazard-prone regions worldwide and offers international implications for long-term disaster governance in line with the Sendai Framework, the Sustainable Development Goals, and the Paris Agreement.
Keywords
Disaster risk reduction
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Disaster-related policy
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Multinomial logit model
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Policy portfolio
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Public support
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Shrinking city
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Tadahiro Okuyama.
Sustaining Disaster Risk Reduction in Shrinking Cities: Policy Evidence from Rikuzentakata, Japan.
International Journal of Disaster Risk Science 1-14 DOI:10.1007/s13753-026-00700-6
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