Modelling and managing systemic risks in supply chains

Kanogkan Leerojanaprapa, Robert Van Der Meer, Lesley Walls

Research output: Contribution to conferencePaper

Abstract

A structured review of the supply chain and risk management literature supports an analysis of the sources and types of risks anticipated in supply chains and networks. We discuss alternative modelling approaches, such as Bayesian Belief Nets (BBN), System Dynamics, Fault and Event Trees, which are evaluated against the criteria characterizing systemic risks that emerge from the literature review. Finally, we briefly present an empirical pilot case study is conducted with a public sector organization in charge of a pharmaceutical distribution network to explore the feasibility of a BBN modelling approach.

Conference

Conference18th International Conference of the European Operations Management Association, 3-6 July 2011, University of Cambridge
CountryUnited Kingdom
CityCambridge
Period3/07/116/07/11

Fingerprint

Systemic risk
Modeling
Supply chain
Supply risk management
Fault
Literature review
Supply network
Distribution network
Pharmaceuticals
System dynamics
Supply chain management
Public sector organizations
Charge

Keywords

  • supply chains
  • Bayesian belief nets
  • risk management

Cite this

Leerojanaprapa, K., Van Der Meer, R., & Walls, L. (2011). Modelling and managing systemic risks in supply chains. Paper presented at 18th International Conference of the European Operations Management Association, 3-6 July 2011, University of Cambridge, Cambridge, United Kingdom.
Leerojanaprapa, Kanogkan ; Van Der Meer, Robert ; Walls, Lesley. / Modelling and managing systemic risks in supply chains. Paper presented at 18th International Conference of the European Operations Management Association, 3-6 July 2011, University of Cambridge, Cambridge, United Kingdom.
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Leerojanaprapa, K, Van Der Meer, R & Walls, L 2011, 'Modelling and managing systemic risks in supply chains' Paper presented at 18th International Conference of the European Operations Management Association, 3-6 July 2011, University of Cambridge, Cambridge, United Kingdom, 3/07/11 - 6/07/11, .

Modelling and managing systemic risks in supply chains. / Leerojanaprapa, Kanogkan; Van Der Meer, Robert; Walls, Lesley.

2011. Paper presented at 18th International Conference of the European Operations Management Association, 3-6 July 2011, University of Cambridge, Cambridge, United Kingdom.

Research output: Contribution to conferencePaper

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AU - Leerojanaprapa, Kanogkan

AU - Van Der Meer, Robert

AU - Walls, Lesley

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N2 - A structured review of the supply chain and risk management literature supports an analysis of the sources and types of risks anticipated in supply chains and networks. We discuss alternative modelling approaches, such as Bayesian Belief Nets (BBN), System Dynamics, Fault and Event Trees, which are evaluated against the criteria characterizing systemic risks that emerge from the literature review. Finally, we briefly present an empirical pilot case study is conducted with a public sector organization in charge of a pharmaceutical distribution network to explore the feasibility of a BBN modelling approach.

AB - A structured review of the supply chain and risk management literature supports an analysis of the sources and types of risks anticipated in supply chains and networks. We discuss alternative modelling approaches, such as Bayesian Belief Nets (BBN), System Dynamics, Fault and Event Trees, which are evaluated against the criteria characterizing systemic risks that emerge from the literature review. Finally, we briefly present an empirical pilot case study is conducted with a public sector organization in charge of a pharmaceutical distribution network to explore the feasibility of a BBN modelling approach.

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Leerojanaprapa K, Van Der Meer R, Walls L. Modelling and managing systemic risks in supply chains. 2011. Paper presented at 18th International Conference of the European Operations Management Association, 3-6 July 2011, University of Cambridge, Cambridge, United Kingdom.