Probabilistic Model for Assessing the Effects of the Disruptive Events on the Viability of the Agri-Food Supply Chains: The Case of Lithuania

Disruptive events may be critical to supply chains as they may not be viable enough to sustain the challenges. Public support is often offered in order to increase the viability of supply chains. This is particularly important in the context of agri-food supply chains that are crucial for food security. This article proposes a novel framework for the assessment of agri-food products' supply chain viability during various disruptive external effects. A proposed method is built on the complex and sophisticated expert evaluation processing technique refined by Monte Carlo simulation. The practical applicability of the proposed framework lies in the fact that the viability of all stages of agri-food supply chains is being assessed separately. Thus, it can be applied to both short and long supply chains. The method was tested by evaluating the effects of COVID-19 and the Ukraine war on the viability of Lithuanian agri-food supply chains. The results show that most of the negative factors arise from increased energy consumption in the agri-food sector. Positive effects were also observed indicating slightly increased production outputs, which should not be directly associated with the disruptive effects of COVID-19 or the Ukraine war, but rather with the ability of Lithuanian agri-food producers to maintain production activities uninterrupted.

Automated summary

This article proposes a novel framework for assessing the viability of agri-food supply chains in the face of disruptive events. The method utilizes Monte Carlo simulation and expert evaluation to assess the viability of different stages of the supply chains. The framework is applicable to both short and long supply chains and has practical value. The evaluation of Lithuanian agri-food supply chains under the effects of COVID-19 and the Ukraine war reveals increased energy consumption as a major negative factor, but also shows slightly increased production outputs due to uninterrupted production activities.