@inproceedings{8817c6c2512846cdb523600442a9e065,
title = "A new modelling approach of evaluating preventive and reactive strategies for mitigating supply chain risks",
abstract = "Supply chains are becoming more complex and vulnerable due to globalization and interdependency between different risks. Existing studies have focused on identifying different preventive and reactive strategies for mitigating supply chain risks and advocating the need for adopting specific strategy under a particular situation. However, current research has not addressed the issue of evaluating an optimal mix of preventive and reactive strategies taking into account their relative costs and benefits within the supply network setting of interconnected firms and organizations. We propose a new modelling approach of evaluating different combinations of such strategies using Bayesian belief networks. This technique helps in determining an optimal solution on the basis of maximum improvement in the network expected loss. We have demonstrated our approach through a simulation study and discussed practical and managerial implications.",
keywords = "Bayesian belief networks, network expected loss, preventive and reactive strategies, simulation study, supply chain risks",
author = "Abroon Qazi and John Quigley and Alex Dickson and Barbara Gaudenzi",
note = "The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-24264-4_39; 6th International Conference on Computational Logistics, ICCL 2015 ; Conference date: 23-09-2015 Through 25-09-2015",
year = "2015",
month = oct,
day = "20",
doi = "10.1007/978-3-319-24264-4_39",
language = "English",
isbn = "9783319242637",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "569--585",
editor = "Francesco Corman and Stefan Vo{\ss} and Negenborn, {Rudy R.}",
booktitle = "Computational Logistics",
}