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A Method for Formulizing Disaster Evacuation Demand Curves Based on SI Model

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  • Yulei Song

    (MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Xuedong Yan

    (MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

The prediction of evacuation demand curves is a crucial step in the disaster evacuation plan making, which directly affects the performance of the disaster evacuation. In this paper, we discuss the factors influencing individual evacuation decision making (whether and when to leave) and summarize them into four kinds: individual characteristics, social influence, geographic location, and warning degree. In the view of social contagion of decision making, a method based on Susceptible-Infective (SI) model is proposed to formulize the disaster evacuation demand curves to address both social influence and other factors’ effects. The disaster event of the “Tianjin Explosions” is used as a case study to illustrate the modeling results influenced by the four factors and perform the sensitivity analyses of the key parameters of the model. Some interesting phenomena are found and discussed, which is meaningful for authorities to make specific evacuation plans. For example, due to the lower social influence in isolated communities, extra actions might be taken to accelerate evacuation process in those communities.

Suggested Citation

  • Yulei Song & Xuedong Yan, 2016. "A Method for Formulizing Disaster Evacuation Demand Curves Based on SI Model," IJERPH, MDPI, vol. 13(10), pages 1-21, October.
  • Handle: RePEc:gam:jijerp:v:13:y:2016:i:10:p:986-:d:80126
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    References listed on IDEAS

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    1. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    2. Hasan, Samiul & Ukkusuri, Satish V., 2011. "A threshold model of social contagion process for evacuation decision making," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1590-1605.
    3. David Hirshleifer & Siew Hong Teoh, 2003. "Herd Behaviour and Cascading in Capital Markets: a Review and Synthesis," European Financial Management, European Financial Management Association, vol. 9(1), pages 25-66, March.
    4. Mustafa Anil Yazici & Kaan Ozbay, 2008. "Evacuation Modelling in the United States: Does the Demand Model Choice Matter?," Transport Reviews, Taylor & Francis Journals, vol. 28(6), pages 757-779, March.
    5. Elaine Vaughan, 1995. "The Significance of Socioeconomic and Ethnic Diversity for the Risk Communication Process," Risk Analysis, John Wiley & Sons, vol. 15(2), pages 169-180, April.
    6. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    7. Lindell, Michael K., 2008. "EMBLEM2: An empirically based large scale evacuation time estimate model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 140-154, January.
    8. Michael K. Lindell & Ronald W. Perry, 2012. "The Protective Action Decision Model: Theoretical Modifications and Additional Evidence," Risk Analysis, John Wiley & Sons, vol. 32(4), pages 616-632, April.
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