Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies
Qazi, Abroon and Quigley, John and Dickson, Alex and Önsel Ekici, Şule (2016) Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies. European Journal of Operational Research, 259 (1). 189–204. ISSN 0377-2217 (https://doi.org/10.1016/j.ejor.2016.10.023)
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Abstract
In this paper, we introduce an integrated supply chain risk management process that is grounded in the theoretical framework of Bayesian Belief Networks capturing interdependency between risks and risk mitigation strategies, and integrating all stages of the risk management process. The proposed process is unique in four different ways: instead of mapping the supply network, it makes use of Failure Modes and Effects Analysis to model the risk network which is feasible for modelling global supply chains; it is driven by new dependency based risk measures that can effectively capture the network wide impact of risks for prioritisation; it utilises the concept of Shapley value from the field of cooperative game theory to determine a fair allocation of resources to the critical risks identified; and the process helps in prioritising potential risk mitigation strategies (both preventive and reactive) subject to budget and resource constraints. We demonstrate its application through a simulation study.
ORCID iDs
Qazi, Abroon ORCID: https://orcid.org/0000-0003-4609-8712, Quigley, John ORCID: https://orcid.org/0000-0002-7253-8470, Dickson, Alex ORCID: https://orcid.org/0000-0001-9386-9036 and Önsel Ekici, Şule;-
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Item type: Article ID code: 58145 Dates: DateEvent20 October 2016Published20 October 2016Published Online13 October 2016AcceptedSubjects: Social Sciences > Industries. Land use. Labor > Risk Management Department: Strathclyde Business School > Management Science
Strathclyde Business School > EconomicsDepositing user: Pure Administrator Date deposited: 14 Oct 2016 09:43 Last modified: 11 Nov 2024 18:01 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/58145