長期間データと構造方程式モデリングを用いた洪水避難行動のメカニズムの検討
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中居 楓子
Understanding evacuation behaviors is crucial in disaster risks reduction as empirical studies indicated that people who are expected to evacuate often do not and vice versa. There is limited understanding on the strengths and underlying mechanisms of predictors of evacuation behaviors as existing literature focused on the characteristics of who evacuate. Thus, this project aims to examine a hypothesized causal model to elucidate the mechanisms leading to evacuation intentions in various case studies with longitudinal data, using structural equation model with latent variables, questionnaire survey data in four case studies including Nagano, Da Nang, and Manila, and longitudinal data over two different periods of time (2025 – 2028). Such materials and methods can provide strong evidence for causal inference of the hypothesized model. This project will (1) examine the causal inference of the proposed model to quantify the effects of predictors on evacuation intentions, (2) test the model consistency for a broad ripple effect on academia and society to (3) provide valuable insights for future research direction and policy recommendations.
変更のために新しい申請を保存します。 This will save a new application on the system for a modification.
申請中の研究者は表示されません。 / Pending researchers are not shown.
ツアオ ブクイェンアン / 東京大学生産技術研究所
申請中のデータセットは表示されません。 / Pending datasets are not shown.
PAREA-Zip郵便番号界・代表点データ（全国、2022年版）
年次報告の内容はメンバーのみ表示されます。