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Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns

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  • Dmitry Ivanov

Abstract

Sourcing strategy analysis in the settings of supply chain (SC) flexibility in regard to single vs. dual sourcing has been a well-explored area over the last two decades. In recent years, single vs. dual sourcing analysis has been increasingly introduced in SC disruption management. Since most of the decision-support models for SC sourcing strategy adaptation in the case of disruptions presume real-time information and coordination, the issues of big data and business intelligence needs to be included into the consideration. A SC simulation model with consideration of capacity disruption and big data along with experimental results are presented. Based on both literature analysis and modelling example, managerial insights are derived. A set of sensitivity experiments allows us to illustrate the model's behaviour. The analysis suggests recommendation on using single sourcing, capacity flexibility and dual sourcing for different combinations of demand and inventory patterns. The paper is concluded by summarising the most important insights and outlining future research agenda.

Suggested Citation

  • Dmitry Ivanov, 2017. "Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 11(1), pages 24-43.
  • Handle: RePEc:ids:ijisma:v:11:y:2017:i:1:p:24-43
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    Citations

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    Cited by:

    1. Dmitry Ivanov & Alexandre Dolgui, 2022. "Stress testing supply chains and creating viable ecosystems," Operations Management Research, Springer, vol. 15(1), pages 475-486, June.
    2. Aarti Singh & Ratri Parida, 2022. "Decision-Making Models for Healthcare Supply Chain Disruptions: Review and Insights for Post-pandemic Era," International Journal of Global Business and Competitiveness, Springer, vol. 17(2), pages 130-141, December.
    3. Babai, M. Zied & Ivanov, Dmitry & Kwon, Oh Kang, 2023. "Optimal ordering quantity under stochastic time-dependent price and demand with a supply disruption: A solution based on the change of measure technique," Omega, Elsevier, vol. 116(C).
    4. Efpraxia D. Zamani & Conn Smyth & Samrat Gupta & Denis Dennehy, 2023. "Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review," Annals of Operations Research, Springer, vol. 327(2), pages 605-632, August.
    5. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    6. Xu, Jinou & Pero, Margherita & Fabbri, Margherita, 2023. "Unfolding the link between big data analytics and supply chain planning," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    7. Vaibhav S. Narwane & Rakesh D. Raut & Sachin Kumar Mangla & Manoj Dora & Balkrishna E. Narkhede, 2023. "Risks to Big Data Analytics and Blockchain Technology Adoption in Supply Chains," Annals of Operations Research, Springer, vol. 327(1), pages 339-374, August.
    8. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    9. Dixit, Vijaya & Verma, Priyanka & Tiwari, Manoj Kumar, 2020. "Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure," International Journal of Production Economics, Elsevier, vol. 227(C).
    10. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    11. Can Ding & Li Liu & Yi Zheng & Jianxiu Liao & Wenxing Huang, 2022. "Role of Distribution Centers Disruptions in New Retail Supply Chain: An Analysis Experiment," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    12. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    13. Riccardo Aldrighetti & Ilenia Zennaro & Serena Finco & Daria Battini, 2019. "Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 81-102, December.

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