Networks and Spatial Economics

, Volume 17, Issue 2, pp 645–680 | Cite as

Heterogeneity Within and Across Households in Hurricane Evacuation Response

  • David S. DixonEmail author
  • Pallab Mozumder
  • William F. Vásquez
  • Hugh Gladwin


A survey of Houston-area households reveals responses to Hurricane Ike in 2008 were as diverse as the households themselves. Review of evacuation literature shows this remains a fundamental problem. In our analysis no clear correlations between household attributes and evacuation motivators emerge unless the respondents are organized into subpopulations based on household attributes and the stated concerns of survey respondents. These subpopulations overlap so that most households fall within multiple classifications, evidence that heterogeneity across households is also present within them. To address heterogeneity within households, an information content metric (information entropy) is considered a proxy for issue saliency. Focusing on the most salient responses to survey questions makes it possible to isolate some of the factors important in the decision to evacuate and the characteristics of the households for which those factors are most important. Regression analysis of the most salient issues of the most concerned respondents informs the creation of behavioral rules for an agent-based model populated with the survey data. The relative strengths of the risk-averting behavior rules are tuned through Monte Carlo simulations using the actual evacuation time of each household as the fitness metric.


Hurricane Natural disaster Evacuation Survey Information theory Network game theory Agent-based modeling 



The authors wish to acknowledge support from the National Science Foundation (Award #0838683, #1204762), from Florida Division of Emergency Management (DEM), and from the International Hurricane Research Center at Florida International University, Miami, Florida. Thanks to the Center for Advanced Research Computing (CARC) at UNM for supercomputer time and support. Thanks also to two anonymous reviewers for extremely helpful comments. The opinions expressed here are solely those of the authors.

Technical Note Entropy and ABM time series plots created in R. All other graphics created in Stata. All regressions run in Stata except the logit regression of the 66,880 simulation results, which was done in R using glm with quasibinomial error distribution and link function.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • David S. Dixon
    • 1
    Email author
  • Pallab Mozumder
    • 2
  • William F. Vásquez
    • 3
  • Hugh Gladwin
    • 4
  1. 1.Department of EconomicsUniversity of New MexicoAlbuquerqueUSA
  2. 2.Department of Earth and Environment and Department of EconomicsFlorida International UniversityMiamiUSA
  3. 3.Department of EconomicsFairfield UniversityFairfieldUSA
  4. 4.Department of Global and Sociocultural StudiesFlorida International UniversityMiamiUSA

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