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Simulating the effects of social networks on a population’s hurricane evacuation participation

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  • Michael Widener
  • Mark Horner
  • Sara Metcalf

Abstract

Scientists have noted that recent shifts in the earth’s climate have resulted in more extreme weather events, like stronger hurricanes. Such powerful storms disrupt societal function and result in a tremendous number of casualties, as demonstrated by recent hurricane experience in the US Planning for and facilitating evacuations of populations forecast to be impacted by hurricanes is perhaps the most effective strategy for reducing risk. A potentially important yet relatively unexplored facet of people’s evacuation decision-making involves the interpersonal communication processes that affect whether at-risk residents decide to evacuate. While previous research has suggested that word-of-mouth effects are limited, data supporting these assertions were collected prior to the widespread adoption of digital social media technologies. This paper argues that the influence of social network effects on evacuation decisions should be revisited given the potential of new social media for impacting and augmenting information dispersion through real-time interpersonal communication. Using geographic data within an agent-based model of hurricane evacuation in Bay County, Florida, we examine how various types of social networks influence participation in evacuation. It is found that strategies for encouraging evacuation should consider the social networks influencing individuals during extreme events, as it can be used to increase the number of evacuating residents. Copyright Springer-Verlag 2013

Suggested Citation

  • Michael Widener & Mark Horner & Sara Metcalf, 2013. "Simulating the effects of social networks on a population’s hurricane evacuation participation," Journal of Geographical Systems, Springer, vol. 15(2), pages 193-209, April.
  • Handle: RePEc:kap:jgeosy:v:15:y:2013:i:2:p:193-209
    DOI: 10.1007/s10109-012-0170-3
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    References listed on IDEAS

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    1. Eisenman, D.P. & Cordasco, K.M. & Asch, S. & Golden, J.F. & Glik, D., 2007. "Disaster planning and risk communication with vulnerable communities: lessons from Hurricane Katrina," American Journal of Public Health, American Public Health Association, vol. 97(S1), pages 109-115.
    2. Urbina, Elba & Wolshon, Brian, 2003. "National review of hurricane evacuation plans and policies: a comparison and contrast of state practices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(3), pages 257-275, March.
    3. Xuwei Chen & John Meaker & F. Zhan, 2006. "Agent-Based Modeling and Analysis of Hurricane Evacuation Procedures for the Florida Keys," 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. 38(3), pages 321-338, July.
    4. Widener, Michael J. & Horner, Mark W., 2011. "A hierarchical approach to modeling hurricane disaster relief goods distribution," Journal of Transport Geography, Elsevier, vol. 19(4), pages 821-828.
    5. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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    Cited by:

    1. Yu Han & Kevin Ash & Liang Mao & Zhong-Ren Peng, 2020. "An agent-based model for community flood adaptation under uncertain sea-level rise," Climatic Change, Springer, vol. 162(4), pages 2257-2276, October.
    2. Md Tawfiq Sarwar & Panagiotis Ch. Anastasopoulos & Satish V. Ukkusuri & Pamela Murray-Tuite & Fred L. Mannering, 2018. "A statistical analysis of the dynamics of household hurricane-evacuation decisions," Transportation, Springer, vol. 45(1), pages 51-70, January.
    3. Rambha, Tarun & Nozick, Linda K. & Davidson, Rachel, 2021. "Modeling hurricane evacuation behavior using a dynamic discrete choice framework," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 75-100.
    4. Troy Curry & Arie Croitoru & Andrew Crooks & Anthony Stefanidis, 2019. "Exodus 2.0: crowdsourcing geographical and social trails of mass migration," Journal of Geographical Systems, Springer, vol. 21(1), pages 161-187, March.

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    More about this item

    Keywords

    Hurricane evacuation; Agent-based model; Social networks; Social media; Q54; C63; H31;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household

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