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Strategies for customer service level protection under multi-echelon supply chain disruption risk


  • Schmitt, Amanda J.


We model a multi-echelon system where disruptions can occur at any stage and evaluate multiple strategies for protecting customer service if a disruption should occur. The strategies considered take advantage of the network itself and include satisfying demand from an alternate location in the network, procuring material or transportation from an alternate source or route, and holding strategic inventory reserves throughout the network. Unmet demand is modeled using a mix of backordering and lost sales. We conduct numerical analysis and provide recommendations on selecting strategic mitigation methods to diminish the impact of disruptions on customer service. We demonstrate that the greatest service level improvements can be made by providing both proactive inventory placement to cover short disruptions or the start of long disruptions, and reactive back-up methods to help the supply chain recover after long or permanent disruptions.

Suggested Citation

  • Schmitt, Amanda J., 2011. "Strategies for customer service level protection under multi-echelon supply chain disruption risk," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1266-1283, September.
  • Handle: RePEc:eee:transb:v:45:y:2011:i:8:p:1266-1283

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    References listed on IDEAS

    1. Ramesh Bollapragada & Uday S. Rao & Jun Zhang, 2004. "Managing Inventory and Supply Performance in Assembly Systems with Random Supply Capacity and Demand," Management Science, INFORMS, vol. 50(12), pages 1729-1743, December.
    2. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    3. Schmitt, Amanda J. & Snyder, Lawrence V. & Shen, Zuo-Jun Max, 2010. "Inventory systems with stochastic demand and supply: Properties and approximations," European Journal of Operational Research, Elsevier, vol. 206(2), pages 313-328, October.
    4. Chu, Peter & Yang, Kuo-Lung & Liang, Shing-Ko & Niu, Thomas, 2004. "Note on inventory model with a mixture of back orders and lost sales," European Journal of Operational Research, Elsevier, vol. 159(2), pages 470-475, December.
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    Cited by:

    1. Qi, Lian & Lee, Kangbok, 2015. "Supply chain risk mitigations with expedited shipping," Omega, Elsevier, vol. 57(PA), pages 98-113.
    2. Cardoso, Sónia R. & Paula Barbosa-Póvoa, Ana & Relvas, Susana & Novais, Augusto Q., 2015. "Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty," Omega, Elsevier, vol. 56(C), pages 53-73.
    3. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    4. repec:spr:joinma:v:29:y:2018:i:4:d:10.1007_s10845-015-1128-3 is not listed on IDEAS
    5. Yanyan Yang & Shenle Pan & Eric Ballot, 2016. "Performance evaluation of interconnected logistics networks confronted to hub disruptions," Post-Print hal-01320641, HAL.
    6. Ebrahim Nejad, Alireza & Niroomand, Iman & Kuzgunkaya, Onur, 2014. "Responsive contingency planning in supply risk management by considering congestion effects," Omega, Elsevier, vol. 48(C), pages 19-35.
    7. repec:eee:transe:v:102:y:2017:i:c:p:13-37 is not listed on IDEAS
    8. Schmitt, Thomas G. & Kumar, Sanjay & Stecke, Kathryn E. & Glover, Fred W. & Ehlen, Mark A., 2017. "Mitigating disruptions in a multi-echelon supply chain using adaptive ordering," Omega, Elsevier, vol. 68(C), pages 185-198.
    9. Bendul, Julia C. & Skorna, Alexander C.H., 2016. "Exploring impact factors of shippers’ risk prevention activities: A European survey in transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 206-223.
    10. Mohammaddust, Faeghe & Rezapour, Shabnam & Farahani, Reza Zanjirani & Mofidfar, Mohammad & Hill, Alex, 2017. "Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 632-653.
    11. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    12. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 0. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-26.
    13. Zhang, Zhi-Hai & Unnikrishnan, Avinash, 2016. "A coordinated location-inventory problem in closed-loop supply chain," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 127-148.
    14. repec:eee:transb:v:110:y:2018:i:c:p:60-78 is not listed on IDEAS
    15. Rika Ampuh Hadiguna, 2012. "Decision support framework for risk assessment of sustainable supply chain," International Journal of Logistics Economics and Globalisation, Inderscience Enterprises Ltd, vol. 4(1/2), pages 35-54.
    16. Shahabi, Mehrdad & Unnikrishnan, Avinash & Jafari-Shirazi, Ehsan & Boyles, Stephen D., 2014. "A three level location-inventory problem with correlated demand," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 1-18.


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