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Accounting for spatial correlation in tsunami evacuation destination choice: a case study of the Great East Japan Earthquake

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  • Giancarlos Troncoso Parady

    (The University of Tokyo)

  • Eiji Hato

    (The University of Tokyo)

Abstract

This article analyzes the tsunami evacuation destination choice process, using as a case study the Great East Japan Earthquake of 2011. The contribution of this article is twofold. First, it sheds some light on the choice mechanism behind tsunami evacuation destination choice, an understudied aspect of the evacuation process. Second, and from a theoretical perspective, it addresses the issue of spatial correlation in discrete choice models. A spatially correlated logit model is estimated, where the allocation parameter is specified as a function of proximity and inter-zone altitude difference to capture more adequately unobserved similarities among alternatives in the specific context of tsunami evacuation.

Suggested Citation

  • Giancarlos Troncoso Parady & Eiji Hato, 2016. "Accounting for spatial correlation in tsunami evacuation destination choice: a case study of the Great East Japan Earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 797-807, November.
    • Handle: RePEc:spr:nathaz:v:84:y:2016:i:2:d:10.1007_s11069-016-2457-z
    DOI: 10.1007/s11069-016-2457-z
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    References listed on IDEAS

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    1. Michel Bierlaire, 2006. "A theoretical analysis of the cross-nested logit model," Annals of Operations Research, Springer, vol. 144(1), pages 287-300, April.
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    3. John C. Whitehead & Bob Edwards & Marieke Van Willigen & John R. Maiolo & Kenneth Wilson & Kevin T. Smith, 2000. "“Heading for Higher Ground: Factors Affecting Real and Hypothetical Hurricane Evacuation Behavior,”," Working Papers 0006, East Carolina University, Department of Economics.
    4. Bekhor, Shlomo & Prashker, Joseph N., 2008. "GEV-based destination choice models that account for unobserved similarities among alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 243-262, March.
    5. Adam Pel & Michiel Bliemer & Serge Hoogendoorn, 2012. "A review on travel behaviour modelling in dynamic traffic simulation models for evacuations," Transportation, Springer, vol. 39(1), pages 97-123, January.
    6. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
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    Cited by:

    1. Wang, Qingyi & Wallace, Stein W., 2022. "Non-compliance in transit-based evacuation pick-up point assignments," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    2. Dingde Xu & Wenfeng Zhou & Xin Deng & Zhixing Ma & Zhuolin Yong & Cheng Qin, 2020. "Information credibility, disaster risk perception and evacuation willingness of rural households in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2865-2882, September.
    3. Junji Urata & Adam J. Pel, 2018. "People's Risk Recognition Preceding Evacuation and Its Role in Demand Modeling and Planning," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 889-905, May.
    4. Simona Mannucci & Federica Rosso & Alessandro D’Amico & Gabriele Bernardini & Michele Morganti, 2022. "Flood Resilience and Adaptation in the Built Environment: How Far along Are We?," Sustainability, MDPI, vol. 14(7), pages 1-22, March.

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