IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2304.05290.html
   My bibliography  Save this paper

Adapting to Disruptions: Flexibility as a Pillar of Supply Chain Resilience

Author

Listed:
  • Ambra Amico
  • Luca Verginer
  • Giona Casiraghi
  • Giacomo Vaccario
  • Frank Schweitzer

Abstract

Supply chain disruptions cause shortages of raw material and products. To increase resilience, i.e., the ability to cope with shocks, substituting goods in established supply chains can become an effective alternative to creating new distribution links. We demonstrate its impact on supply deficits through a detailed analysis of the US opioid distribution system. Reconstructing 40 billion empirical distribution paths, our data-driven model allows a unique inspection of policies that increase the substitution flexibility. Our approach enables policymakers to quantify the trade-off between increasing flexibility, i.e., reduced supply deficits, and increasing complexity of the supply chain, which could make it more expensive to operate.

Suggested Citation

  • Ambra Amico & Luca Verginer & Giona Casiraghi & Giacomo Vaccario & Frank Schweitzer, 2023. "Adapting to Disruptions: Flexibility as a Pillar of Supply Chain Resilience," Papers 2304.05290, arXiv.org.
    • Handle: RePEc:arx:papers:2304.05290
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2304.05290
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Frank Schweitzer & Georges Andres & Giona Casiraghi & Christoph Gote & Ramona Roller & Ingo Scholtes & Giacomo Vaccario & Christian Zingg, 2022. "Modeling Social Resilience: Questions, Answers, Open Problems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 25(08), pages 1-50, December.
    2. Rebekka Burkholz & Frank Schweitzer, 2019. "International crop trade networks: The impact of shocks and cascades," Papers 1901.05872, arXiv.org.
    3. Ingo Scholtes & Nicolas Wider & René Pfitzner & Antonios Garas & Claudio J. Tessone & Frank Schweitzer, 2014. "Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    4. Tang, Christopher & Tomlin, Brian, 2008. "The power of flexibility for mitigating supply chain risks," International Journal of Production Economics, Elsevier, vol. 116(1), pages 12-27, November.
    5. Stéphane Hallegatte, 2014. "Modeling the Role of Inventories and Heterogeneity in the Assessment of the Economic Costs of Natural Disasters," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 152-167, January.
    6. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    7. Tobias Bier & Anne Lange & Christoph H. Glock, 2020. "Methods for mitigating disruptions in complex supply chain structures: a systematic literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 58(6), pages 1835-1856, March.
    8. Schweitzer, Frank, 2022. "Group relations, resilience and the I Ching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    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. 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.
    2. 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.
    3. Lydia Novoszel & Tina Wakolbinger, 2022. "Meta-analysis of Supply Chain Disruption Research," SN Operations Research Forum, Springer, vol. 3(1), pages 1-25, March.
    4. Kihyung Kim & Li Zhao, 2021. "Filtering Facepiece Respirator Supply Chain Management Framework in a Disaster Such as COVID-19," Societies, MDPI, vol. 11(4), pages 1-15, November.
    5. Muhammad Junaid & Ye Xue & Muzzammil Wasim Syed & Ji Zu Li & Muhammad Ziaullah, 2019. "A Neutrosophic AHP and TOPSIS Framework for Supply Chain Risk Assessment in Automotive Industry of Pakistan," Sustainability, MDPI, vol. 12(1), pages 1-26, December.
    6. Domenico Delli Gatti & Elisa Grugni, 2022. "Breaking bad: supply chain disruptions in a streamlined agent-based model," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1446-1473, October.
    7. Zuhal Cilingir Uk & Cigdem Basfirinci & Amit Mitra, 2022. "Weighted Interpretive Structural Modeling for Supply Chain Risk Management: An Application to Logistics Service Providers in Turkey," Logistics, MDPI, vol. 6(3), pages 1-22, August.
    8. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    9. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2021. "The impact of congestion on protection decisions in supply networks under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    10. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    11. Aziz Barhmi & Omar Hajaji, 2023. "Multidisciplinary Approach to Supply Chain Resilience: Conceptualization and Scale Development," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 43-69.
    12. Muhammad Rahies Khan & Amir Manzoor, 2021. "Application and Impact of New Technologies in the Supply Chain Management During COVID-19 Pandemic: A Systematic Literature Review," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(2), pages 277-292.
    13. Panayotis Christidis & Álvaro Gomez Losada, 2019. "Email Based Institutional Network Analysis: Applications and Risks," Social Sciences, MDPI, vol. 8(11), pages 1-14, November.
    14. Basu R, Jothi & Abdulrahman, Muhammad D. & Yuvaraj, M., 2023. "Improving agility and resilience of automotive spares supply chain: The additive manufacturing enabled truck model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    15. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    16. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    17. David Nortes Martínez & Frédéric Grelot & Pauline Bremond & Stefano Farolfi & Juliette Rouchier, 2021. "Are interactions important in estimating flood damage to economic entities? The case of wine-making in France," Post-Print hal-03609616, HAL.
    18. Berger, Niklas & Schulze-Schwering, Stefan & Long, Elisa & Spinler, Stefan, 2023. "Risk management of supply chain disruptions: An epidemic modeling approach," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1036-1051.
    19. Rabbani, Fereshteh & Khraisha, Tamer & Abbasi, Fatemeh & Jafari, Gholam Reza, 2021. "Memory effects on link formation in temporal networks: A fractional calculus approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    20. Marco Bardoscia & Fabio Caccioli & Juan Ignacio Perotti & Gianna Vivaldo & Guido Caldarelli, 2016. "Distress Propagation in Complex Networks: The Case of Non-Linear DebtRank," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-12, October.

    More about this item

    Statistics

    Access and download statistics

    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:arx:papers:2304.05290. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.