IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v118y2023ics0305048323000282.html
   My bibliography  Save this article

Reshore or not Reshore: A Stochastic Programming Approach to Supply Chain Optimization

Author

Listed:
  • Sawik, Tadeusz

Abstract

This paper presents a scenario-based stochastic mixed integer programming model for risk-neutral or risk-averse optimization of supply chain reshoring to domestic region, under the ripple effect propagated from a foreign disruption source region. The reshoring decisions with respect to tier-one suppliers of parts and tier-zero OEM (Original Equipment Manufacturer) assembly plants are considered under disruptions in supply, manufacturing, logistics and demand rippling across the entire supply chain. The proposed innovative approach integrates strategic supply chain reshoring and operational supply chain scheduling, which allows the decision maker to evaluate the operational impact of the strategic decision. Results of computational experiments, partially modeled after a supply chain reshoring problem in the smartphone industry, are provided. The findings indicate that reshoring decisions are strongly dependent on the level of government subsidy for capital expenditure and for risk-neutral reshoring, a portfolio of supply chain nodes with positive expected net savings can be considered only. In general, the reshored supply chain can better meet domestic market demand. Moreover, full reshoring of a supply chain improves its business as usual performance and even partial reshoring mitigates the impact of the ripple effect. However, for risk-averse decision-making, if reshoring is incapable of reducing worst-case cost, in particular, worst-case lost sales, no reshoring is selected.

Suggested Citation

  • Sawik, Tadeusz, 2023. "Reshore or not Reshore: A Stochastic Programming Approach to Supply Chain Optimization," Omega, Elsevier, vol. 118(C).
    • Handle: RePEc:eee:jomega:v:118:y:2023:i:c:s0305048323000282
    DOI: 10.1016/j.omega.2023.102863
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048323000282
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2023.102863?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. Jan Stentoft & Jan Olhager & Jussi Heikkilä & Lisa Thoms, 2016. "Manufacturing backshoring: a systematic literature review," Operations Management Research, Springer, vol. 9(3), pages 53-61, December.
    2. 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.
    3. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    4. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A multi-layer Bayesian network method for supply chain disruption modelling in the wake of the COVID-19 pandemic," International Journal of Production Research, Taylor & Francis Journals, vol. 60(17), pages 5258-5276, September.
    5. 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.
    6. 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).
    7. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    8. Kim, Yun Geon & Chung, Byung Do, 2022. "Closed-loop supply chain network design considering reshoring drivers," Omega, Elsevier, vol. 109(C).
    9. Pearce, John A., 2014. "Why domestic outsourcing is leading America's reemergence in global manufacturing," Business Horizons, Elsevier, vol. 57(1), pages 27-36.
    10. Tadeusz Sawik, 2023. "A stochastic optimisation approach to maintain supply chain viability under the ripple effect," International Journal of Production Research, Taylor & Francis Journals, vol. 61(8), pages 2452-2469, April.
    11. Paolo Barbieri & Albachiara Boffelli & Stefano Elia & Luciano Fratocchi & Matteo Kalchschmidt & Danny Samson, 2020. "What can we learn about reshoring after Covid-19?," Operations Management Research, Springer, vol. 13(3), pages 131-136, December.
    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. Liu, Ming & Ding, Yueyu & Chu, Feng & Dolgui, Alexandre & Zheng, Feifeng, 2024. "Robust actions for improving supply chain resilience and viability," Omega, Elsevier, vol. 123(C).
    2. S. Hati & K. Maity, 2024. "Production inventory control model for deteriorating complementary and substitute items with shortage," OPSEARCH, Springer;Operational Research Society of India, vol. 61(4), pages 2023-2054, December.

    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. Ivanov, Dmitry, 2024. "Supply chain resilience: Conceptual and formal models drawing from immune system analogy," Omega, Elsevier, vol. 127(C).
    2. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    3. 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).
    4. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).
    5. Brusset, Xavier & Ivanov, Dmitry & Jebali, Aida & La Torre, Davide & Repetto, Marco, 2023. "A dynamic approach to supply chain reconfiguration and ripple effect analysis in an epidemic," International Journal of Production Economics, Elsevier, vol. 263(C).
    6. Ivanov, Dmitry, 2023. "Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability," International Journal of Production Economics, Elsevier, vol. 263(C).
    7. Chervenkova, Tanya & Ivanov, Dmitry, 2023. "Adaptation strategies for building supply chain viability: A case study analysis of the global automotive industry re-purposing during the COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    8. Kim, Yun Geon & Chung, Byung Do, 2022. "Closed-loop supply chain network design considering reshoring drivers," Omega, Elsevier, vol. 109(C).
    9. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    10. Sinha, Priyank & Kumar, Sameer & Chandra, Charu, 2023. "Strategies for ensuring required service level for COVID-19 herd immunity in Indian vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 304(1), pages 339-352.
    11. Dachs, Bernhard & Kinkel, Steffen & Jäger, Angela, 2019. "Bringing it all back home? Backshoring of manufacturing activities and the adoption of Industry 4.0 technologies," Journal of World Business, Elsevier, vol. 54(6), pages 1-1.
    12. 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).
    13. Clavijo-Buritica, Nicolás & Triana-Sanchez, Laura & Escobar, John Willmer, 2023. "A hybrid modeling approach for resilient agri-supply network design in emerging countries: Colombian coffee supply chain," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    14. El Baz, Jamal & Ruel, Salomée, 2021. "Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era," International Journal of Production Economics, Elsevier, vol. 233(C).
    15. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    16. McIvor, Ronan & Bals, Lydia, 2021. "A multi-theory framework for understanding the reshoring decision," International Business Review, Elsevier, vol. 30(6).
    17. 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).
    18. 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.
    19. 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).
    20. Gebhardt, Maximilian & Spieske, Alexander & Kopyto, Matthias & Birkel, Hendrik, 2022. "Increasing global supply chains’ resilience after the COVID-19 pandemic: Empirical results from a Delphi study," Journal of Business Research, Elsevier, vol. 150(C), pages 59-72.

    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:jomega:v:118:y:2023:i:c:s0305048323000282. 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/375/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.