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Demand Stratification and Prediction of Evacuees after Earthquakes

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  • Shaoqing Geng

    (Department of Logistics Management and Engineering, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Hanping Hou

    (Department of Logistics Management and Engineering, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

Abstract

In recent years, frequent natural disasters have brought huge losses to human lives and property, directly affecting social stability and economic development. Since the driving factor of disaster management operations is speed, it will face severe challenges and tremendous pressure when matching the supply of emergency resources with the demand. However, it is difficult to figure out the demands of the affected area until the initial post-disaster assessment is completed and demand is constantly changing. The focus of this paper is to stratify the evacuation needs and predict the number of evacuees and supplies demanded after an earthquake. This research takes a large-scale earthquake as an example to analyze the characteristics of evacuation demand stratification and the factors that affect the demands of evacuees. The forecast model for the number of evacuees is selected and improved. Moreover, combining the influencing factors of materials demand and the number of evacuees, a forecast model of materials demand for evacuees is constructed. The proposed model is used in the case of the Ya’an earthquake in China to estimate the number of evacuees and the daily need for emergency supplies.

Suggested Citation

  • Shaoqing Geng & Hanping Hou, 2021. "Demand Stratification and Prediction of Evacuees after Earthquakes," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:8837-:d:610229
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    1. Filipe Batista e Silva & Sérgio Freire & Marcello Schiavina & Konštantín Rosina & Mario Alberto Marín-Herrera & Lukasz Ziemba & Massimo Craglia & Eric Koomen & Carlo Lavalle, 2020. "Uncovering temporal changes in Europe’s population density patterns using a data fusion approach," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    2. Chia-Nan Wang & Thanh-Tuan Dang & Ngoc-Ai-Thy Nguyen & Thi-Thu-Hong Le, 2020. "Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces," Sustainability, MDPI, vol. 12(24), pages 1-24, December.
    3. Lin, Lexin & Nilsson, Anders & Sjölin, Johan & Abrahamsson, Marcus & Tehler, Henrik, 2015. "On the perceived usefulness of risk descriptions for decision-making in disaster risk management," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 48-55.
    4. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2019. "Understanding public transport satisfaction: Using Maslow's hierarchy of (transit) needs," Transport Policy, Elsevier, vol. 81(C), pages 75-94.
    5. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    6. Nurul Nnadiah Zakaria & Mahmod Othman & Rajalingam Sokkalingam & Hanita Daud & Lazim Abdullah & Evizal Abdul Kadir, 2019. "Markov Chain Model Development for Forecasting Air Pollution Index of Miri, Sarawak," Sustainability, MDPI, vol. 11(19), pages 1-11, September.
    7. Li, Anna C.Y. & Nozick, Linda & Xu, Ningxiong & Davidson, Rachel, 2012. "Shelter location and transportation planning under hurricane conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 715-729.
    8. Dilsu Binnaz Ozkapici & Mustafa Alp Ertem & Haluk Aygüneş, 2016. "Intermodal humanitarian logistics model based on maritime transportation in Istanbul," 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. 83(1), pages 345-364, August.
    9. Taskin, Selda & Lodree Jr., Emmett J., 2010. "Inventory decisions for emergency supplies based on hurricane count predictions," International Journal of Production Economics, Elsevier, vol. 126(1), pages 66-75, July.
    10. Sheu, Jiuh-Biing & Pan, Cheng, 2014. "A method for designing centralized emergency supply network to respond to large-scale natural disasters," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 284-305.
    11. C. Chen & T. Chen & Y. Chen & S. Yu & P. Chung, 2013. "Storm surge prediction with management information systems: A case study of estimating value and observations system," 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. 66(2), pages 1009-1027, March.
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    2. Haotian Zheng & Shuchuan Zhang & Junqi Zhu & Ziyan Zhu & Xin Fang, 2022. "Evacuation in Buildings Based on BIM: Taking a Fire in a University Library as an Example," IJERPH, MDPI, vol. 19(23), pages 1-21, December.

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