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Provincial evaluation of vulnerability to geological disaster in China and its influencing factors: a three-stage DEA-based analysis

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  • Mingze Li
  • Jun Lv
  • Xin Chen
  • Nan Jiang

Abstract

China is a country with frequent natural disasters. In order to prevent the losses caused by disaster, this paper plans to make evaluation on vulnerability to geological disaster in 31 provinces in China based on overcoming the disadvantages of traditional data envelopment analysis evaluation methods. The research selected some relevant indexes in China from 2004 to 2010, including the frequency of geological disasters, GDP, population density, personal injury and property loss so as to analyze vulnerability to geological disaster in each province (municipality), and it found that geological vulnerability in China presented an overall pattern of East China > Central China > West China. In addition, it found from the analysis of the influencing factors of vulnerability that industrial development and scientific and technological advancement could reduce vulnerability to geological disasters significantly, while the growth in per-capita GDP and mean sea level could increase vulnerability to geological disasters to a certain extent. Meanwhile, the research indicated that the investment in the prevention and control of geological disasters in China did not have significant effects on the whole vulnerability to geological disasters. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Mingze Li & Jun Lv & Xin Chen & Nan Jiang, 2015. "Provincial evaluation of vulnerability to geological disaster in China and its influencing factors: a three-stage DEA-based analysis," 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. 79(3), pages 1649-1662, December.
    • Handle: RePEc:spr:nathaz:v:79:y:2015:i:3:p:1649-1662
    DOI: 10.1007/s11069-015-1917-1
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    as
    1. Le–Le Zou, 2012. "The impacting factors of vulnerability to natural hazards in China: an analysis based on structural equation model," 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. 62(1), pages 57-70, May.
    2. Schumacher, Ingmar & Strobl, Eric, 2011. "Economic development and losses due to natural disasters: The role of hazard exposure," Ecological Economics, Elsevier, vol. 72(C), pages 97-105.
    3. Dale Dominey-Howes, 2002. "Documentary and Geological Records of Tsunamis in the Aegean Sea Region of Greece and their Potential Value to Risk Assessment and Disaster Management," 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. 25(3), pages 195-224, March.
    4. Dapeng Huang & Renhe Zhang & Zhiguo Huo & Fei Mao & Youhao E & Wei Zheng, 2012. "An assessment of multidimensional flood vulnerability at the provincial scale in China based on the DEA method," 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. 64(2), pages 1575-1586, November.
    5. Gorman, Michael F. & Ruggiero, John, 2008. "Evaluating US state police performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1031-1037, June.
    6. Fikret Berkes, 2007. "Understanding uncertainty and reducing vulnerability: lessons from resilience thinking," 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. 41(2), pages 283-295, May.
    7. Jianyi Huang & Yi Liu & Li Ma & Fei Su, 2013. "Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model," 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. 65(1), pages 115-134, January.
    8. Ruggiero, John, 1998. "A new approach for technical efficiency estimation in multiple output production," European Journal of Operational Research, Elsevier, vol. 111(2), pages 369-380, December.
    9. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    10. Le-Le Zou & Yi-Ming Wei, 2009. "Impact assessment using DEA of coastal hazards on social-economy in Southeast Asia," 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. 48(2), pages 167-189, February.
    11. José Aceves-Quesada & Jesús Díaz-Salgado & Jorge López-Blanco, 2007. "Vulnerability assessment in a volcanic risk evaluation in Central Mexico through a multi-criteria-GIS approach," 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. 40(2), pages 339-356, February.
    12. Nahra, Tammie A. & Mendez, David & Alexander, Jeffrey A., 2009. "Employing super-efficiency analysis as an alternative to DEA: An application in outpatient substance abuse treatment," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1097-1106, August.
    13. Xiao-Chen Yuan & Qian Wang & Ke Wang & Bing Wang & Ju-Liang Jin & Yi-Ming Wei, 2013. "China's regional vulnerability to drought and its mitigation strategies under climate change: Data envelopment analysis and analytic hierarchy process integrated approach," CEEP-BIT Working Papers 44, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    14. Zhu, Joe, 2001. "Super-efficiency and DEA sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 129(2), pages 443-455, March.
    15. Mei Xue & Patrick T. Harker, 2002. "Note: Ranking DMUs with Infeasible Super-Efficiency DEA Models," Management Science, INFORMS, vol. 48(5), pages 705-710, May.
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    5. Yuting Yang & Gang Mei, 2022. "A Deep Learning-Based Approach for a Numerical Investigation of Soil–Water Vertical Infiltration with Physics-Informed Neural Networks," Mathematics, MDPI, vol. 10(16), pages 1-19, August.
    6. Siqi Wan & Zhile Shu & Xin Zhang & Wenwu Zhong & Haikuan Wu & Shun Kang & Tingyue Zheng, 2024. "Research on the Disaster Management of China’s Ethnic Minority Autonomous Regions in the Development of Modernization Construction—Taking Mabian Yi Autonomous County in Southern Sichuan as an Example," Sustainability, MDPI, vol. 16(16), pages 1-26, August.
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