Kohji Tanaka
Biographic Data
| ID | 9960853 |
|---|---|
| NAME | Kohji Tanaka |
| GIVEN NAMES | Kohji |
| FAMILY NAME | Tanaka |
| SIGNATURE | TANAKA K |
| AFFILIATIONS | Portland State University |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
When flood warnings fail
Flood warnings are often assumed—particularly within traditional average-effect models—to prompt uniform behavioral responses, yet real-world evidence suggests that message effectiveness varies widely across the population. This study empirically identifies and explains such heterogeneity using a factorial survey experiment ( n = 1,671) conducted among residents in flood-prone regions of Japan. We estimate finite mixture beta regression models to…
Who pays for preparedness? Valuing disaster app features through a factorial survey experiment in flood-prone communities
This study evaluates public preferences for next-generation disaster preparedness apps using a factorial survey experiment in flood-prone Japanese communities. The analysis first reveals a fundamental heterogeneity in public receptiveness, identifying two distinct segments: a small "receptive" minority (approx. 20%) willing to consider adoption, and a large "unreceptive" majority (approx. 80%) that rejects the app regardless of its features or pr…
No prominent works on this page.
When flood warnings fail
Flood warnings are often assumed—particularly within traditional average-effect models—to prompt uniform behavioral responses, yet real-world evidence suggests that message effectiveness varies widely across the population. This study empirically identifies and explains such heterogeneity using a factorial survey experiment ( n = 1,671) conducted among residents in flood-prone regions of Japan. We estimate finite mixture beta regression models to…
Who pays for preparedness? Valuing disaster app features through a factorial survey experiment in flood-prone communities
This study evaluates public preferences for next-generation disaster preparedness apps using a factorial survey experiment in flood-prone Japanese communities. The analysis first reveals a fundamental heterogeneity in public receptiveness, identifying two distinct segments: a small "receptive" minority (approx. 20%) willing to consider adoption, and a large "unreceptive" majority (approx. 80%) that rejects the app regardless of its features or pr…
Disaster Management and Resilience (2 works) · Flood Risk Assessment and Management (2 works) · Agricultural risk and resilience (1 work) · CLARITY (1 work) · Cognition (1 work) · Distrust (1 work) · Factorial (1 work) · Factorial analysis (1 work) · Flood myth (1 work) · Hazard (1 work)