IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v58y2020i20p6370-6398.html
   My bibliography  Save this article

Fuzzy cognitive maps approach for analysing the domino effect of factors affecting supply chain resilience: a fashion industry case study

Author

Listed:
  • Maurizio Bevilacqua
  • Filippo Emanuele Ciarapica
  • Giulio Marcucci
  • Giovanni Mazzuto

Abstract

The domino effect that occurs among the concepts that affect Supply Chain Resilience has only been marginally analysed, and no conceptual models have been proposed in the literature. In this work, a conceptual model for analysing this domino effect is developed. The method aims to identify which supply chain concepts can support the containment of disruptions and how these concepts affect one another. The proposed methodology is based on Fuzzy Cognitive Maps. The Cognitive Maps tool enables us to connect multidimensional and multidisciplinary concepts (e.g. sources of risk, disruption factors, supply chain management practices and other aspects). Moreover, this tool allows company managers to develop a detailed understanding of a system's behaviour and to explicitly consider the mind models of different players in the supply chain. A case study of the fashion industry supply chain is used to illustrate the application of the proposed method in an operating context. The proposed method enables a company to evaluate the hidden chain reaction of causes behind the most important factors that, from a single trigger event, are able to harm the entire Supply Chain. Through analysis of the causal relationships that this methodology highlights, decision makers can examine the domino effect among the concepts that influence Supply Chain Resilience in a step-by-step manner.

Suggested Citation

  • Maurizio Bevilacqua & Filippo Emanuele Ciarapica & Giulio Marcucci & Giovanni Mazzuto, 2020. "Fuzzy cognitive maps approach for analysing the domino effect of factors affecting supply chain resilience: a fashion industry case study," International Journal of Production Research, Taylor & Francis Journals, vol. 58(20), pages 6370-6398, October.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:20:p:6370-6398
    DOI: 10.1080/00207543.2019.1680893
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2019.1680893
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2019.1680893?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.

    Citations

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


    Cited by:

    1. Bag, Surajit & Sabbir Rahman, Muhammad & Rogers, Helen & Srivastava, Gautam & Harm Christiaan Pretorius, Jan, 2023. "Climate change adaptation and disaster risk reduction in the garment industry supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    2. Fabio Di Carlo & Giovanni Mazzuto & Maurizio Bevilacqua & Filippo Emanuele Ciarapica, 2021. "Retrofitting a Process Plant in an Industry 4.0 Perspective for Improving Safety and Maintenance Performance," Sustainability, MDPI, vol. 13(2), pages 1-18, January.
    3. Chih-Hung Hsu & Ming-Ge Li & Ting-Yi Zhang & An-Yuan Chang & Shu-Zhen Shangguan & Wan-Ling Liu, 2022. "Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework," Mathematics, MDPI, vol. 10(8), pages 1-35, April.
    4. Hu, Man & Liu, Xue-Xin & Jia, Fu, 2024. "Optimal Emergency Order Policy for Supply Disruptions in the Semiconductor Industry," International Journal of Production Economics, Elsevier, vol. 272(C).
    5. Tomás F. Espino-Rodríguez, 2023. "Research on Outsourcing by Hotel Firms: Current State and Future Directions," Tourism and Hospitality, MDPI, vol. 4(1), pages 1-15, January.
    6. Beata Milewska, 2022. "The Impact of the COVID-19 Pandemic on Supply Chains in the Example of Polish Clothing Companies in the Context of Sustainable Development," Sustainability, MDPI, vol. 14(3), pages 1-19, February.
    7. Jia, Nanfei & An, Haizhong & Gao, Xiangyun & Liu, Donghui & Chang, Hao, 2023. "The main transmission paths of price fluctuations for tungsten products along the industry chain," Resources Policy, Elsevier, vol. 80(C).

    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:taf:tprsxx:v:58:y:2020:i:20:p:6370-6398. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.