IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v74y2021ics0301420717301940.html
   My bibliography  Save this article

Resilient procurement planning for supply chains: A case study for sourcing a critical mineral material

Author

Listed:
  • Fattahi, Mohammad

Abstract

This study develops a multi-stage stochastic program to determine optimal selection of suppliers, sourcing strategy, and order allocation in a multi-period supply chain planning under operational and disruption risks. Option contract and spot market are considered as two alternatives for sourcing a critical raw material under an uncertain decision-making environment. Final products’ demand and the material's market price are stochastic, and capacity of unreliable suppliers varies randomly because of possible disruptions. For uncertainty modeling, discrete scenarios are generated via a simulation approach and then, a scenario reduction technique is used to construct a suitable scenario tree. To obtain a resilient planning, fortification of suppliers and option contract are exploited as mitigation strategies. Further, the level of supply chain's risk is quantified through a risk measure and limited by risk constraints. Computational results are presented on a real-life supply chain including multiple mines as suppliers and zinc-smelting plants that produce zinc ingots and powder. Using the computational studies and sensitivity analysis, the applicability of the stochastic model, the performance of risk-measurement policies, and the importance of mitigation strategies are investigated to drive some managerial insights.

Suggested Citation

  • Fattahi, Mohammad, 2021. "Resilient procurement planning for supply chains: A case study for sourcing a critical mineral material," Resources Policy, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420717301940
    DOI: 10.1016/j.resourpol.2017.10.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420717301940
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2017.10.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Hantao & Ritchken, Peter & Wang, Yunzeng, 2009. "Option and forward contracting with asymmetric information: Valuation issues in supply chains," European Journal of Operational Research, Elsevier, vol. 197(1), pages 134-148, August.
    2. Dawn Barnes-Schuster & Yehuda Bassok & Ravi Anupindi, 2002. "Coordination and Flexibility in Supply Contracts with Options," Manufacturing & Service Operations Management, INFORMS, vol. 4(3), pages 171-207, May.
    3. Sawik, Tadeusz, 2014. "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing," Omega, Elsevier, vol. 43(C), pages 83-95.
    4. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    5. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    6. P D Berger & A Z Zeng, 2006. "Single versus multiple sourcing in the presence of risks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(3), pages 250-261, March.
    7. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    8. Yu, Haisheng & Zeng, Amy Z. & Zhao, Lindu, 2009. "Single or dual sourcing: decision-making in the presence of supply chain disruption risks," Omega, Elsevier, vol. 37(4), pages 788-800, August.
    9. Lapko, Yulia & Trucco, Paolo & Nuur, Cali, 2016. "The business perspective on materials criticality: Evidence from manufacturers," Resources Policy, Elsevier, vol. 50(C), pages 93-107.
    10. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    11. Meena, P.L. & Sarmah, S.P., 2013. "Multiple sourcing under supplier failure risk and quantity discount: A genetic algorithm approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 84-97.
    12. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    13. M. Fattahi & M. Mahootchi & S. M. Moattar Husseini, 2016. "Integrated strategic and tactical supply chain planning with price-sensitive demands," Annals of Operations Research, Springer, vol. 242(2), pages 423-456, July.
    14. Maqbool Dada & Nicholas C. Petruzzi & Leroy B. Schwarz, 2007. "A Newsvendor's Procurement Problem when Suppliers Are Unreliable," Manufacturing & Service Operations Management, INFORMS, vol. 9(1), pages 9-32, August.
    15. Massari, Stefania & Ruberti, Marcello, 2013. "Rare earth elements as critical raw materials: Focus on international markets and future strategies," Resources Policy, Elsevier, vol. 38(1), pages 36-43.
    16. Lawrence V. Snyder & Zümbül Atan & Peng Peng & Ying Rong & Amanda J. Schmitt & Burcu Sinsoysal, 2016. "OR/MS models for supply chain disruptions: a review," IISE Transactions, Taylor & Francis Journals, vol. 48(2), pages 89-109, February.
    17. Christian van Delft & Jean-Philippe Vial, 2004. "A practical implementation of stochastic programming: an application to the evaluation of option contracts in supply chains," Post-Print hal-00471409, HAL.
    18. Kai Huang & Shabbir Ahmed, 2009. "The Value of Multistage Stochastic Programming in Capacity Planning Under Uncertainty," Operations Research, INFORMS, vol. 57(4), pages 893-904, August.
    19. Berger, Paul D. & Gerstenfeld, Arthur & Zeng, Amy Z., 2004. "How many suppliers are best? A decision-analysis approach," Omega, Elsevier, vol. 32(1), pages 9-15, February.
    20. Verma, Rohit & Pullman, Madeleine E., 1998. "An analysis of the supplier selection process," Omega, Elsevier, vol. 26(6), pages 739-750, December.
    21. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    22. Ho-Yin Mak & Zuo-Jun Shen, 2012. "Risk diversification and risk pooling in supply chain design," IISE Transactions, Taylor & Francis Journals, vol. 44(8), pages 603-621.
    23. Firouz, Mohammad & Keskin, Burcu B. & Melouk, Sharif H., 2017. "An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments," Omega, Elsevier, vol. 70(C), pages 77-93.
    24. Holger Heitsch & Werner Römisch, 2009. "Scenario tree reduction for multistage stochastic programs," Computational Management Science, Springer, vol. 6(2), pages 117-133, May.
    25. Inderfurth, Karl & Kelle, Peter, 2011. "Capacity reservation under spot market price uncertainty," International Journal of Production Economics, Elsevier, vol. 133(1), pages 272-279, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Ping-Kuo & Ye, Yong & Wen, Ming-Hui, 2023. "Efficiency of metaverse on the improvement of the green procurement policy of semiconductor supply chain – based on behaviour perspective," Resources Policy, Elsevier, vol. 86(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 2018. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 763-788, April.
    2. Maheswar Singh Mahapatra & Pravash Chandra Pradhan & J. K. Jha, 2022. "Sourcing decisions with order allocation under supply disruption risk considering quantitative and qualitative criteria," Operational Research, Springer, vol. 22(4), pages 3291-3333, September.
    3. Svoboda, Josef & Minner, Stefan & Yao, Man, 2021. "Typology and literature review on multiple supplier inventory control models," European Journal of Operational Research, Elsevier, vol. 293(1), pages 1-23.
    4. Sawik, Tadeusz, 2015. "On the fair optimization of cost and customer service level in a supply chain under disruption risks," Omega, Elsevier, vol. 53(C), pages 58-66.
    5. PrasannaVenkatesan, S. & Goh, M., 2016. "Multi-objective supplier selection and order allocation under disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 124-142.
    6. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    7. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    8. Jin Sung Rha, 2020. "Trends of Research on Supply Chain Resilience: A Systematic Review Using Network Analysis," Sustainability, MDPI, vol. 12(11), pages 1-27, May.
    9. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    10. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    11. 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.
    12. Cheramin, Meysam & Saha, Apurba Kumar & Cheng, Jianqiang & Paul, Sanjoy Kumar & Jin, Hongyue, 2021. "Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    13. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2017. "An assessment of supply chain disruption mitigation strategies," International Journal of Production Economics, Elsevier, vol. 184(C), pages 210-230.
    14. Chao Fang & Xiangxiang Liao & Min Xie, 2016. "A hybrid risks-informed approach for the selection of supplier portfolio," International Journal of Production Research, Taylor & Francis Journals, vol. 54(7), pages 2019-2034, April.
    15. Bodendorf, Frank & Sauter, Maximilian & Franke, Jörg, 2023. "A mixed methods approach to analyze and predict supply disruptions by combining causal inference and deep learning," International Journal of Production Economics, Elsevier, vol. 256(C).
    16. Merzifonluoglu, Yasemin, 2015. "Risk averse supply portfolio selection with supply, demand and spot market volatility," Omega, Elsevier, vol. 57(PA), pages 40-53.
    17. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    18. Guertler, Benjamin & Spinler, Stefan, 2015. "When does operational risk cause supply chain enterprises to tip? A simulation of intra-organizational dynamics," Omega, Elsevier, vol. 57(PA), pages 54-69.
    19. Belleh Fontem & Megan Price, 2021. "Joint client selection and contract design for a risk-averse commodity broker in a two-echelon supply chain," Annals of Operations Research, Springer, vol. 307(1), pages 111-138, December.
    20. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420717301940. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.