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A composite indicator model to assess natural disaster risks in industry on a spatial level

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  • Mirjam Merz
  • Michael Hiete
  • Tina Comes
  • Frank Schultmann

Abstract

In the event of natural disasters, industrial production sites can be affected by both direct physical damage and indirect damage. The indirect damage, which often exceeds the direct ones in value, mainly arises from business interruptions resulting from the impairment of information and material flows as well as from domino effects in interlaced supply chains. The importance of industry for society and the domino effects often result in severe economic, social, and environmental consequences of industrial disasters making industrial risk management an important task for risk managers at the administrative level (e.g. civil protection authorities). Since the possible industrial disaster damage depends not only on hazard and exposure but also on the vulnerability of a system, an effective and efficient industrial risk management requires information about the system's regionalized vulnerability. This paper presents a new methodology for structural industrial vulnerability assessment based on production factors that enables to assess the regional industrial disaster vulnerability. In order to capture industry-specific vulnerability factors and to account for the processes underlying regional industrial vulnerability, a two-stage approach is developed. This approach combines a composite indicator model to assess sector-specific vulnerability indices ( V s ) with a new regionalization method. The composite indicator model is based on methodologies from the field of multicriteria decision analysis (MultiAttribute Value Theory) and the Decision-Making Trial and Evaluation Laboratory Method is applied to correct the ( V s ) for interdependencies among the indicators. Finally, the developed approach is applied to an exemplar case study and the industrial vulnerability of 44 administrative districts in the German federal state of Baden-Wuerttemberg is assessed.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:jriskr:v:16:y:2013:i:9:p:1077-1099
    DOI: 10.1080/13669877.2012.737820
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    References listed on IDEAS

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    1. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
    2. Maxx Dilley & Robert S. Chen & Uwe Deichmann & Arthur L. Lerner-Lam & Margaret Arnold, 2005. "Natural Disaster Hotspots: A Global Risk Analysis," World Bank Publications - Books, The World Bank Group, number 7376.
    3. 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.
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    Cited by:

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    2. Jieun Ryu & Eun Joo Yoon & Chan Park & Dong Kun Lee & Seong Woo Jeon, 2017. "A Flood Risk Assessment Model for Companies and Criteria for Governmental Decision-Making to Minimize Hazards," Sustainability, MDPI, vol. 9(11), pages 1-26, November.
    3. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    4. Arshavir Avagyan & Hasmik Manandyan & Aleksandr Arakelyan & Artak Piloyan, 2018. "Toward a disaster risk assessment and mapping in the virtual geographic environment of Armenia," 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. 92(1), pages 283-309, May.

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