Quantification of supply chain risks : development and application of a novel risk management framework
Qazi, Abroon Jamal and Quigley, John and Dickson, Alexander (2014) Quantification of supply chain risks : development and application of a novel risk management framework. In: 19th Annual Logistics Research Network (LRN) Conference and PhD Workshop 2014, 2014-09-03 - 2014-09-05, University of Huddersfield.
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Abstract
Purpose: Supply chain risk management is still an active area of research that necessitates application of existing risk quantification techniques in established fields for potential application in the research area. This study is focused on bridging the research gap through development of a novel risk management framework that merges the two quantitative techniques of Bayesian belief network and Game theory. Bayesian belief networks capture the interdependency between various risk factors while Game theory models the risks associated with conflicting incentives of stakeholders in a supply network. The proposed framework segregates risk drivers, events and consequences and captures their interdependency. Development project of Boeing 787 aircraft was a unique venture in terms of its unconventional supply chain and unproven technology. Instead of the realization of anticipated shorter development time and reduced costs, the project turned out to be a fiasco. A new term ‘game theoretic risks’ has been coined to acknowledge the risks associated with conflicting incentives of various stakeholders in a supply network. Research Approach: This study has focused on a review of the literature for establishing the research gap followed by designing of a novel framework (conceptual model) for quantification and management of supply chain risks. Subsequently, the model has been applied on the development project of Boeing 787 aircraft. Findings and Originality: The developed framework is unique in its design merging two quantitative techniques in the field of Supply Chain Risk Management. Application of the novel framework on a case study of Boeing 787 project revealed its merits in terms of capturing the dynamics of interacting risk factors. Bayesian belief network is a useful modelling technique for risk quantification capturing the interdependency between various risks. Game theoretic modelling provides an opportunity to model the risks associated with conflicting incentives of the stakeholders within a supply network. Game theory based modelling captured the behaviour of suppliers in relation to the uncertainty about cost functions and the final response of Boeing to the delays caused by suppliers. The results clearly manifested importance of the game theoretic risks and as there was no policy to align the incentives of suppliers in Boeing 787 project, there was a major delay causing financial penalty to Boeing. Furthermore, lack of management expertise in Supply Chain Risk Management was a major factor for the higher development cost. It has been proved that lack of information in a supply chain affects the desired objectives of a project. To our best knowledge, such a framework has never been developed and applied in the field of Supply Chain Risk Management. Research Impact: The output of this study will help researchers model the supply chain risks in a more realistic way and stimulate further research in this direction. Practical Impact: The application of our developed model on a case study reveals its practical impact. Had the Boeing considered the holistic view of the supply chain risks, the project delay and financial loss would not have materialized. Our model can be utilized in supply networks of other industries.
ORCID iDs
Qazi, Abroon Jamal ORCID: https://orcid.org/0000-0003-4609-8712, Quigley, John ORCID: https://orcid.org/0000-0002-7253-8470 and Dickson, Alexander ORCID: https://orcid.org/0000-0001-9386-9036;-
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Item type: Conference or Workshop Item(Paper) ID code: 50445 Dates: DateEventSeptember 2014PublishedSubjects: Social Sciences > Industries. Land use. Labor > Risk Management Department: Strathclyde Business School > Management Science
Strathclyde Business School > EconomicsDepositing user: Pure Administrator Date deposited: 19 Nov 2014 14:57 Last modified: 11 Nov 2024 16:42 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/50445