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

Mirjam Merz, Michael Hiete, Tina Comes and Frank Schultmann

Journal of Risk Research, 2013, vol. 16, issue 9, 1077-1099

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.

Date: 2013
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DOI: 10.1080/13669877.2012.737820

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