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Network theory-based analysis of risk interactions in large engineering projects

Author

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  • Fang, Chao
  • Marle, Franck
  • Zio, Enrico
  • Bocquet, Jean-Claude

Abstract

This paper presents an approach based on network theory to deal with risk interactions in large engineering projects. Indeed, such projects are exposed to numerous and interdependent risks of various nature, which makes their management more difficult. In this paper, a topological analysis based on network theory is presented, which aims at identifying key elements in the structure of interrelated risks potentially affecting a large engineering project. This analysis serves as a powerful complement to classical project risk analysis. Its originality lies in the application of some network theory indicators to the project risk management field. The construction of the risk network requires the involvement of the project manager and other team members assigned to the risk management process. Its interpretation improves their understanding of risks and their potential interactions. The outcomes of the analysis provide a support for decision-making regarding project risk management. An example of application to a real large engineering project is presented. The conclusion is that some new insights can be found about risks, about their interactions and about the global potential behavior of the project.

Suggested Citation

  • Fang, Chao & Marle, Franck & Zio, Enrico & Bocquet, Jean-Claude, 2012. "Network theory-based analysis of risk interactions in large engineering projects," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 1-10.
    • Handle: RePEc:eee:reensy:v:106:y:2012:i:c:p:1-10
    DOI: 10.1016/j.ress.2012.04.005
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    References listed on IDEAS

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    3. Eusgeld, Irene & Kröger, Wolfgang & Sansavini, Giovanni & Schläpfer, Markus & Zio, Enrico, 2009. "The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 954-963.
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