IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v173y2023ics1366554523000777.html
   My bibliography  Save this article

An optimization-based methodology equipped with lean tools to strengthen medical supply chain resilience during a pandemic: A case study from Turkey

Author

Listed:
  • Yılmaz, Ömer Faruk
  • Yeni, Fatma Betül
  • Gürsoy Yılmaz, Beren
  • Özçelik, Gökhan

Abstract

Drawing upon economic and environmental sustainability, this study explores how developing the operational resilience of the medical supply chain (MSC) contributes to maintaining healthcare in the face of disruption risks, such as the COVID-19 pandemic. To this end, an optimization-based roadmap is proposed by employing lean tools to achieve and realize MSC resilience. A novel two-stage stochastic optimization model and robust counterpart are developed with the objective of overall cost minimization to cope with the unknowable demand uncertainty represented by scenarios. The reason behind proposing a scenario-based stochastic model is to implement preparedness strategies during the (re)design phase by making strategic and operational level decisions. That being the case, seven cases are generated based on the demand uncertainty intervals along with seven different reliability levels for sensitivity analysis. Computational experiments are conducted through a real case study to compare the centralized and decentralized distribution models in terms of efficiency and responsiveness. The results obtained by the stochastic model and robust counterpart are compared to demonstrate how strong the proposed model is. On top of that, lean tools are used to visualize and analyze the improvement opportunities to contribute to the methodology. By doing so, this paper presents novel theoretical and empirical insights regarding MSC resilience. The computational results emphasize the importance of employing a pre-disruption strategy via the proposed methodology to design a resilient MSC to be prepared for pandemic-related risk. The findings from the sensitivity analysis also verify that regardless of the disruption degree, the developed roadmap with the centralized distribution model leads to up to 40% improvements in terms of the overall cost, order lead time, emission amount, and inventory shortage metrics.

Suggested Citation

  • Yılmaz, Ömer Faruk & Yeni, Fatma Betül & Gürsoy Yılmaz, Beren & Özçelik, Gökhan, 2023. "An optimization-based methodology equipped with lean tools to strengthen medical supply chain resilience during a pandemic: A case study from Turkey," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:transe:v:173:y:2023:i:c:s1366554523000777
    DOI: 10.1016/j.tre.2023.103089
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554523000777
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2023.103089?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. Hamdan, Bayan & Diabat, Ali, 2020. "Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    2. Emily L. Tucker & Mark S. Daskin & Burgunda V. Sweet & Wallace J. Hopp, 2020. "Incentivizing resilient supply chain design to prevent drug shortages: policy analysis using two- and multi-stage stochastic programs," IISE Transactions, Taylor & Francis Journals, vol. 52(4), pages 394-412, April.
    3. Suryawanshi, Pravin & Dutta, Pankaj, 2022. "Optimization models for supply chains under risk, uncertainty, and resilience: A state-of-the-art review and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    4. Salarpour, Mojtaba & Nagurney, Anna, 2021. "A multicountry, multicommodity stochastic game theory network model of competition for medical supplies inspired by the Covid-19 pandemic," International Journal of Production Economics, Elsevier, vol. 236(C).
    5. Koppiahraj Karuppiah & Bathrinath Sankaranarayanan & Syed Mithun Ali, 2022. "Modeling Impacts of COVID-19 in Supply Chain Activities: A Grey-DEMATEL Approach," Sustainability, MDPI, vol. 14(21), pages 1-21, October.
    6. Fattahi, Mohammad & Govindan, Kannan, 2018. "A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: A real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 534-567.
    7. Wang, Changjun & Chen, Shutong, 2020. "A distributionally robust optimization for blood supply network considering disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    8. Ivanov, Dmitry & Pavlov, Alexander & Pavlov, Dmitry & Sokolov, Boris, 2017. "Minimization of disruption-related return flows in the supply chain," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 503-513.
    9. Fariba Goodarzian & Peiman Ghasemi & Angappa Gunasekaren & Ata Allah Taleizadeh & Ajith Abraham, 2022. "A sustainable-resilience healthcare network for handling COVID-19 pandemic," Annals of Operations Research, Springer, vol. 312(2), pages 761-825, May.
    10. Michael K. Lim & Achal Bassamboo & Sunil Chopra & Mark S. Daskin, 2013. "Facility Location Decisions with Random Disruptions and Imperfect Estimation," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 239-249, May.
    11. Fadaki, Masih & Abareshi, Ahmad & Far, Shaghayegh Maleki & Lee, Paul Tae-Woo, 2022. "Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    12. Tadeusz Sawik, 2017. "A portfolio approach to supply chain disruption management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1970-1991, April.
    13. 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).
    14. Shafiee, Mohammad & Zare-Mehrjerdi, Yahia & Govindan, Kannan & Dastgoshade, Sohaib, 2022. "A causality analysis of risks to perishable product supply chain networks during the COVID-19 outbreak era: An extended DEMATEL method under Pythagorean fuzzy environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    15. Yilmaz, Omer Faruk & Ozcelik, Gokhan & Yeni, Fatma Betul, 2020. "Lean holistic fuzzy methodology employing cross-functional worker teams for new product development projects: A real case study from high-tech industry," European Journal of Operational Research, Elsevier, vol. 282(3), pages 989-1010.
    16. 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).
    17. Dmitry Ivanov & Ajay Das, 2020. "Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: a research note," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 13(1), pages 90-102.
    18. Manupati, Vijaya Kumar & Schoenherr, Tobias & Subramanian, Nachiappan & Ramkumar, M. & Soni, Bhanushree & Panigrahi, Suraj, 2021. "A multi-echelon dynamic cold chain for managing vaccine distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    19. Guiyang Zhu & Mabel C. Chou & Christina W. Tsai, 2020. "Lessons Learned from the COVID-19 Pandemic Exposing the Shortcomings of Current Supply Chain Operations: A Long-Term Prescriptive Offering," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    20. Dmitry Ivanov, 2018. "Revealing interfaces of supply chain resilience and sustainability: a simulation study," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3507-3523, May.
    21. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    22. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh, 2019. "An enhanced procedure for managing blood supply chain under disruptions and uncertainties," Annals of Operations Research, Springer, vol. 283(1), pages 1413-1462, December.
    23. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    24. Alexandre Dolgui & Dmitry Ivanov & Maxim Rozhkov, 2020. "Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1285-1301, March.
    25. Yazdekhasti, Amin & Wang, Jun & Zhang, Li & Ma, Junfeng, 2021. "A multi-period multi-modal stochastic supply chain model under COVID pandemic: A poultry industry case study in Mississippi," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    26. Tadeusz Sawik, 2016. "On the risk-averse optimization of service level in a supply chain under disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 98-113, January.
    27. Ivanov, Dmitry & Pavlov, Alexander & Sokolov, Boris, 2014. "Optimal distribution (re)planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics," European Journal of Operational Research, Elsevier, vol. 237(2), pages 758-770.
    28. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    29. Nayeri, Sina & Sazvar, Zeinab & Heydari, Jafar, 2022. "A global-responsive supply chain considering sustainability and resiliency: Application in the medical devices industry," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    30. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    31. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
    32. Songtao Zhang & Panpan Zhang & Min Zhang, 2019. "Fuzzy Emergency Model and Robust Emergency Strategy of Supply Chain System under Random Supply Disruptions," Complexity, Hindawi, vol. 2019, pages 1-10, January.
    33. Masoud Kamalahmadi & Mahour Mellat-Parast, 2016. "Developing a resilient supply chain through supplier flexibility and reliability assessment," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 302-321, January.
    34. Rezapour, Shabnam & Farahani, Reza Zanjirani & Pourakbar, Morteza, 2017. "Resilient supply chain network design under competition: A case study," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1017-1035.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    3. Liu, Ming & Liu, Zhongzheng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Zheng, Feifeng, 2022. "An optimization approach for multi-echelon supply chain viability with disruption risk minimization," Omega, Elsevier, vol. 112(C).
    4. 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.
    5. 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.
    6. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    7. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    8. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    9. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    10. Samani, Mohammad Reza Ghatreh & Hosseini-Motlagh, Seyyed-Mahdi & Homaei, Shamim, 2020. "A reactive phase against disruptions for designing a proactive platelet supply network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    11. Alikhani, Reza & Ranjbar, Amirhossein & Jamali, Amir & Torabi, S. Ali & Zobel, Christopher W., 2023. "Towards increasing synergistic effects of resilience strategies in supply chain network design," Omega, Elsevier, vol. 116(C).
    12. Seyed Hossein Razavi Hajiagha & Hannan Amoozad Mahdiraji & Maryam Behnam & Boshra Nekoughadirli & Rohit Joshi, 2022. "A scenario-based robust time–cost tradeoff model to handle the effect of COVID-19 on supply chains project management," Operations Management Research, Springer, vol. 15(1), pages 357-377, June.
    13. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    14. Muhammad Umar Farooq & Amjad Hussain & Tariq Masood & Muhammad Salman Habib, 2021. "Supply Chain Operations Management in Pandemics: A State-of-the-Art Review Inspired by COVID-19," Sustainability, MDPI, vol. 13(5), pages 1-33, February.
    15. Dmitry Ivanov, 2017. "Simulation-based ripple effect modelling in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2083-2101, April.
    16. Zhu, Xiaoyan & Cao, Yunzhi, 2021. "The optimal recovery-fund based strategy for uncertain supply chain disruptions: A risk-averse two-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    17. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    18. Chen, Li-Ming & Chang, Wei-Lun, 2021. "Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    19. Ramani, Vinay & Ghosh, Debabrata & Sodhi, ManMohan S., 2022. "Understanding systemic disruption from the Covid-19-induced semiconductor shortage for the auto industry," Omega, Elsevier, vol. 113(C).
    20. Ardekani, Zahra Fozouni & Sobhani, Seyed Mohammad Javad & Barbosa, Marcelo Werneck & de Sousa, Paulo Renato, 2023. "Transition to a sustainable food supply chain during disruptions: A study on the Brazilian food companies in the Covid-19 era," International Journal of Production Economics, Elsevier, vol. 257(C).

    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:transe:v:173:y:2023:i:c:s1366554523000777. 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/wps/find/journaldescription.cws_home/600244/description#description .

    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.