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An integrated indicator framework for spatial assessment of industrial and social vulnerability to indirect disaster losses

Author

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  • Bijan Khazai

  • Mirjam Merz
  • Carola Schulz
  • Dietmar Borst

Abstract

The focus of this study is on multi-dimensional vulnerability of regions to indirect disaster losses. An integrated indicator framework has been developed which captures the multi-layered vulnerability drivers in industrial production systems and also accounts for the social fragilities and coping capacities in communities. By combining industrial vulnerability and social vulnerability spatially, and proposing a methodology to account between their interactions, the total vulnerability to indirect risks of regions is revealed. The outcome of the framework is a ranking of industrial sectors and geographic areas according to their vulnerability against indirect losses. It answers the question which of the two affected regions is in a better position to cope with indirect consequences in a disaster. Indicators provide a flexible framework for the comparison and integration of different data types and allow the combination of social as well as economic aspects. Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology was applied to analyze direct and indirect dependencies within the selected social and industrial vulnerability indicators. The hierarchical indicator system has been implemented in a software system based on multi-criteria decision theory (MCDA) with an interactive interface to take into account a broader range of expert judgement. The methodology was applied in a case study in the state of Baden-Wuerttemberg in Germany for 16 different industrial sectors. The approach helps to identify particular vulnerable processes and points out where mitigation measures could be implemented most effectively. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Bijan Khazai & Mirjam Merz & Carola Schulz & Dietmar Borst, 2013. "An integrated indicator framework for spatial assessment of industrial and social vulnerability to indirect disaster losses," 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. 67(2), pages 145-167, June.
  • Handle: RePEc:spr:nathaz:v:67:y:2013:i:2:p:145-167
    DOI: 10.1007/s11069-013-0551-z
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    References listed on IDEAS

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    Cited by:

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    4. Mirjam Merz & Michael Hiete & Tina Comes & Frank Schultmann, 2013. "A composite indicator model to assess natural disaster risks in industry on a spatial level," Journal of Risk Research, Taylor & Francis Journals, vol. 16(9), pages 1077-1099, October.
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    7. Saini Yang & Shuai He & Juan Du & Xiaohua Sun, 2015. "Screening of social vulnerability to natural hazards in China," 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. 76(1), pages 1-18, March.
    8. Yi Ge & Wen Dou & Xiaotao Wang & Yi Chen & Ziyuan Zhang, 2021. "Identifying urban–rural differences in social vulnerability to natural hazards: a case study of China," 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. 108(3), pages 2629-2651, September.
    9. František Zapletal, 2026. "Novel PROMETHEE method with dependent criteria," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 34(1), pages 183-209, March.
    10. Huifang Sun & Yaoguo Dang & Wenxin Mao, 2019. "Identifying key factors of regional agricultural drought vulnerability using a panel data grey combined 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. 98(2), pages 621-642, September.
    11. Jan Kowalski & Marzena Lendo-Siwicka & Zdzisław Skutnik & Dorota Mirosław-Świątek, 2024. "Application of the DEMATEL method for quantitative analysis of risk factors for railway investments in Poland," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-20, May.
    12. Suvojit Dhara & Adrijit Goswami, 2023. "Causal Relationship and Ranking Technique (CRRT): A Novel Group Decision-Making Model and Application in Students’ Performance Assessment in Indian High School Context," Group Decision and Negotiation, Springer, vol. 32(4), pages 835-870, August.
    13. Ming Zhang & Wenbo Xiang & Meilan Chen & Zisen Mao, 2018. "Measuring Social Vulnerability to Flood Disasters in China," Sustainability, MDPI, vol. 10(8), pages 1-14, July.

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