A multi-attribute systemic risk index for comparing and prioritizing chemical industrial areas

G. Reniers, K. Sorensen, W.E.H. Dullaert

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Measures taken to decrease interdependent risks within chemical industrial areas should be based on quantitative data from a holistic (cluster-based) point of view. Therefore, this paper examines the typology of networks representing industrial areas to formulate recommendations to more effectively protect a chemical cluster against existing systemic risks. Chemical industrial areas are modeled as two distinct complex networks and are prioritized by computing two sub-indices with respect to existing systemic safety and security risks (using Domino Danger Units) and supply chain risks (using units from an ordinal expert scale). Subsequently, a Systemic Risk Index for the industrial area is determined employing the Borda algorithm, whereby the systemic risk index considers both a safety and security network risk index and a supply chain network risk index. The developed method allows decreasing systemic risks within chemical industrial areas from a holistic (inter-organizational and/or inter-cluster) perspective. An illustrative example is given. © 2011 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)35-42
JournalReliability Engineering and System Safety
Volume98
Issue number1
DOIs
Publication statusPublished - 2012

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Industrial chemicals
Supply chains
Network security
Complex networks

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A multi-attribute systemic risk index for comparing and prioritizing chemical industrial areas. / Reniers, G.; Sorensen, K.; Dullaert, W.E.H.

In: Reliability Engineering and System Safety, Vol. 98, No. 1, 2012, p. 35-42.

Research output: Contribution to JournalArticleAcademicpeer-review

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AB - Measures taken to decrease interdependent risks within chemical industrial areas should be based on quantitative data from a holistic (cluster-based) point of view. Therefore, this paper examines the typology of networks representing industrial areas to formulate recommendations to more effectively protect a chemical cluster against existing systemic risks. Chemical industrial areas are modeled as two distinct complex networks and are prioritized by computing two sub-indices with respect to existing systemic safety and security risks (using Domino Danger Units) and supply chain risks (using units from an ordinal expert scale). Subsequently, a Systemic Risk Index for the industrial area is determined employing the Borda algorithm, whereby the systemic risk index considers both a safety and security network risk index and a supply chain network risk index. The developed method allows decreasing systemic risks within chemical industrial areas from a holistic (inter-organizational and/or inter-cluster) perspective. An illustrative example is given. © 2011 Elsevier Ltd. All rights reserved.

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