Vulnerabilities and disruptions that are localized in a specific company can lead to consequences along with the entire supply chain, snowballing in magnitude and causing a resilience loss. This study proposes a methodology to unveil the causal relationships that occur among different factors as a result of a disruption and how these causal relationships strengthen or weaken supply chain resilience. This methodology is based on fuzzy cognitive maps capability to link multidimensional and multidisciplinary factors together, providing supply chain managers with a graph structure for understanding the system behaviour. The proposed methodology is applied to a case study in order to explain the research approach and show how the implementation of the fuzzy cognitive maps can provide valuable support in defining casual reactions that generate resilience variations. In particular, an agri-food supply chain is analysed taking into consideration as a disruption the COVID-19 pandemic. A total of 60 principal paths (ripple effects) and 6 cycles influencing agri-food supply chain resilience have been exemplified, highlighting how “Long shelf-life food demand”, “Closure of the Ho.Re.Ca. channel” factors are critical into influencing supply chain resilience. Other results reveal how “panic buying” can instead strengthen agri-food Supply Chain Resilience. The proposed methodology has shown its generality as a holistic approach in the analysis of all type of disruptions in a supply chain.

特定公司局部的漏洞和中断可能会导致整个供应链的后果，其程度会像滚雪球一样越滚越大，并导致弹性损失。本研究提出了一种方法来揭示因中断而导致的不同因素之间发生的因果关系，以及这些因果关系如何增强或削弱供应链的弹性。该方法基于模糊认知图能力，将多维和多学科因素联系在一起，为供应链管理者提供用于理解系统行为的图形结构。所提出的方法应用于案例研究，以解释研究方法，并展示模糊认知图的实施如何为定义产生弹性变化的随意反应提供有价值的支持。特别是，我们对农业食品供应链进行了分析，考虑到了 COVID-19 大流行的破坏。总共举例说明了影响农产品供应链弹性的 60 个主要路径（连锁反应）和 6 个周期，突出了“长保质期食品需求”、“Ho.Re.Ca 的关闭”如何影响农业食品供应链的弹性。渠道”因素对于影响供应链弹性至关重要。其他结果揭示了“恐慌性购买”如何增强农产品供应链的弹性。