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Articles

Evaluation mechanism for structural robustness of supply chain considering disruption propagation

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Pages 135-151 | Received 02 Oct 2014, Accepted 08 Apr 2015, Published online: 29 May 2015

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Xiao-qiu Shi, Wei Long, Yan-yan Li, Ding-shan Deng, Yong-lai Wei & Hua-guo Liu. (2020) Research on supply network resilience considering random and targeted disruptions simultaneously. International Journal of Production Research 58:21, pages 6670-6688.
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Aseem Kinra, Dmitry Ivanov, Ajay Das & Alexandre Dolgui. (2020) Ripple effect quantification by supplier risk exposure assessment. International Journal of Production Research 58:18, pages 5559-5578.
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Seyedmohsen Hosseini, Dmitry Ivanov & Alexandre Dolgui. (2020) Ripple effect modelling of supplier disruption: integrated Markov chain and dynamic Bayesian network approach. International Journal of Production Research 58:11, pages 3284-3303.
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Wen Jun Tan, Allan N. Zhang & Wentong Cai. (2019) A graph-based model to measure structural redundancy for supply chain resilience. International Journal of Production Research 57:20, pages 6385-6404.
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Dmitry Ivanov & Alexandre Dolgui. (2019) Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. International Journal of Production Research 57:15-16, pages 5119-5136.
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Dmitry Ivanov, Alexandre Dolgui & Boris Sokolov. (2019) The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research 57:3, pages 829-846.
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Jessica Olivares Aguila & Waguih ElMaraghy. (2018) Structural complexity and robustness of supply chain networks based on product architecture. International Journal of Production Research 56:20, pages 6701-6718.
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Dmitry Ivanov, Alexandre Dolgui & Boris Sokolov. (2018) Scheduling of recovery actions in the supply chain with resilience analysis considerations. International Journal of Production Research 56:19, pages 6473-6490.
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Ritesh Ojha, Abhijeet Ghadge, Manoj Kumar Tiwari & Umit S. Bititci. (2018) Bayesian network modelling for supply chain risk propagation. International Journal of Production Research 56:17, pages 5795-5819.
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Maurício Fontoura Blos, Robson Marinho da Silva & Hui-Ming Wee. (2018) A framework for designing supply chain disruptions management considering productive systems and carrier viewpoints. International Journal of Production Research 56:15, pages 5045-5061.
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Alexandre Dolgui, Dmitry Ivanov & Boris Sokolov. (2018) Ripple effect in the supply chain: an analysis and recent literature. International Journal of Production Research 56:1-2, pages 414-430.
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Dmitry Ivanov. (2017) Simulation-based ripple effect modelling in the supply chain. International Journal of Production Research 55:7, pages 2083-2101.
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Xiaoling Xu, Jennifer Shang, Haiyan Wang & Wen-Chyuan Chiang. (2016) Optimal production and inventory decisions under demand and production disruptions. International Journal of Production Research 54:1, pages 287-301.
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