Supply chain risk network management: a bayesian belief network and expected utility based approach for managing supply chain risks

Abroon Qazi, Alex Dickson, John Quigley, Barbara Gaudenzi

Research output: Contribution to journalArticle

  • 2 Citations

Abstract

The paper develops and operationalises a supply chain risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting. The process helps in prioritising risks and strategies specific to the decision maker's risk appetite. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. Theoretically grounded in the framework of Bayesian Belief Networks (BBNs) and Expected Utility Theory (EUT), the modelling approach has a number of distinctive characteristics. It utilises a top-down approach of Fault Tree Analysis (FTA). Performance measures are identified first and subsequently connected to risks. A 'probability conditional expected utility' matrix is introduced to reflect the propagation impact of interdependent risks on all performance measures identified. A 'weighted net evaluation of risk mitigation' method is proposed and the method of 'swing weights' is used to capture the tradeoff between the efficacy of strategies and the associated cost keeping in view the decision maker's risk appetite. The approach adapts and integrates techniques from safety and reliability engineering (FTA), decision making under uncertainty (EUT), and multi-criteria decision analysis (swing weights). The merits and challenges associated with the implementation of interdependency based frameworks are discussed. Propositions are presented to elucidate the significance of modelling interdependency between risks and strategies.
LanguageEnglish
Pages24-42
Number of pages19
JournalInternational Journal of Production Economics
Early online date7 Nov 2017
DOIs
StatePublished - 28 Feb 2018

Fingerprint

Network management
Bayesian networks
Supply chains
Fault tree analysis
Expected utility
Bayesian belief networks
Supply chain risk
Decision theory
Risk management
Performance measures
Interdependencies
Decision making
Fault
Modeling
Expected utility theory
Risk appetite
Risk mitigation
Decision maker

Keywords

  • Supply Chain Risk Network Management
  • risk mitigation strategies
  • Bayesian belief networks
  • expected utility theory
  • multiple performance measures

Cite this

@article{07fe28c2007a446888ef8bf649910d0d,
title = "Supply chain risk network management: a bayesian belief network and expected utility based approach for managing supply chain risks",
abstract = "The paper develops and operationalises a supply chain risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting. The process helps in prioritising risks and strategies specific to the decision maker's risk appetite. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. Theoretically grounded in the framework of Bayesian Belief Networks (BBNs) and Expected Utility Theory (EUT), the modelling approach has a number of distinctive characteristics. It utilises a top-down approach of Fault Tree Analysis (FTA). Performance measures are identified first and subsequently connected to risks. A 'probability conditional expected utility' matrix is introduced to reflect the propagation impact of interdependent risks on all performance measures identified. A 'weighted net evaluation of risk mitigation' method is proposed and the method of 'swing weights' is used to capture the tradeoff between the efficacy of strategies and the associated cost keeping in view the decision maker's risk appetite. The approach adapts and integrates techniques from safety and reliability engineering (FTA), decision making under uncertainty (EUT), and multi-criteria decision analysis (swing weights). The merits and challenges associated with the implementation of interdependency based frameworks are discussed. Propositions are presented to elucidate the significance of modelling interdependency between risks and strategies.",
keywords = "Supply Chain Risk Network Management, risk mitigation strategies, Bayesian belief networks, expected utility theory, multiple performance measures",
author = "Abroon Qazi and Alex Dickson and John Quigley and Barbara Gaudenzi",
year = "2018",
month = "2",
day = "28",
doi = "10.1016/j.ijpe.2017.11.008",
language = "English",
pages = "24--42",
journal = "International Journal of Production Economics",
issn = "0925-5273",

}

TY - JOUR

T1 - Supply chain risk network management

T2 - International Journal of Production Economics

AU - Qazi,Abroon

AU - Dickson,Alex

AU - Quigley,John

AU - Gaudenzi,Barbara

PY - 2018/2/28

Y1 - 2018/2/28

N2 - The paper develops and operationalises a supply chain risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting. The process helps in prioritising risks and strategies specific to the decision maker's risk appetite. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. Theoretically grounded in the framework of Bayesian Belief Networks (BBNs) and Expected Utility Theory (EUT), the modelling approach has a number of distinctive characteristics. It utilises a top-down approach of Fault Tree Analysis (FTA). Performance measures are identified first and subsequently connected to risks. A 'probability conditional expected utility' matrix is introduced to reflect the propagation impact of interdependent risks on all performance measures identified. A 'weighted net evaluation of risk mitigation' method is proposed and the method of 'swing weights' is used to capture the tradeoff between the efficacy of strategies and the associated cost keeping in view the decision maker's risk appetite. The approach adapts and integrates techniques from safety and reliability engineering (FTA), decision making under uncertainty (EUT), and multi-criteria decision analysis (swing weights). The merits and challenges associated with the implementation of interdependency based frameworks are discussed. Propositions are presented to elucidate the significance of modelling interdependency between risks and strategies.

AB - The paper develops and operationalises a supply chain risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting. The process helps in prioritising risks and strategies specific to the decision maker's risk appetite. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. Theoretically grounded in the framework of Bayesian Belief Networks (BBNs) and Expected Utility Theory (EUT), the modelling approach has a number of distinctive characteristics. It utilises a top-down approach of Fault Tree Analysis (FTA). Performance measures are identified first and subsequently connected to risks. A 'probability conditional expected utility' matrix is introduced to reflect the propagation impact of interdependent risks on all performance measures identified. A 'weighted net evaluation of risk mitigation' method is proposed and the method of 'swing weights' is used to capture the tradeoff between the efficacy of strategies and the associated cost keeping in view the decision maker's risk appetite. The approach adapts and integrates techniques from safety and reliability engineering (FTA), decision making under uncertainty (EUT), and multi-criteria decision analysis (swing weights). The merits and challenges associated with the implementation of interdependency based frameworks are discussed. Propositions are presented to elucidate the significance of modelling interdependency between risks and strategies.

KW - Supply Chain Risk Network Management

KW - risk mitigation strategies

KW - Bayesian belief networks

KW - expected utility theory

KW - multiple performance measures

UR - http://www.sciencedirect.com/science/journal/09255273

U2 - 10.1016/j.ijpe.2017.11.008

DO - 10.1016/j.ijpe.2017.11.008

M3 - Article

SP - 24

EP - 42

JO - International Journal of Production Economics

JF - International Journal of Production Economics

SN - 0925-5273

ER -