System dynamics model for improving the robustness of a fresh agri-food supply chain to disruptions

[EN] The agri-food sector is subject to various sources of uncertainty and risk that can have a negative impact on its supply chain performance if not properly managed. In order to determine what actions the supply chain (SC) should take to protect itself against risks, it is necessary to analyze wh...

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Detalhes bibliográficos
Autores: Esteso, Ana|||0000-0003-0379-8786, Alemany Díaz, María Del Mar|||0000-0002-0992-8441, Ortiz Bas, Ángel|||0000-0001-5690-0807, Ottati, Fernando
Formato: artículo
Fecha de publicación:2023
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/204528
Acesso em linha:https://riunet.upv.es/handle/10251/204528
Access Level:acceso abierto
Palavra-chave:Agri-food supply chain
Disruption
Robustness
Simulation
System dynamics
ORGANIZACION DE EMPRESAS
Descrição
Resumo:[EN] The agri-food sector is subject to various sources of uncertainty and risk that can have a negative impact on its supply chain performance if not properly managed. In order to determine what actions the supply chain (SC) should take to protect itself against risks, it is necessary to analyze whether the supply chain is robust to them. This paper proposes a tool based on a system dynamics model to determine the robustness of an already designed five-stage fresh agri-food supply chain (AFSC) and its planting planning to disruptions in demand, supply, transport, and the operability of its nodes. The model is validated using the known behavior replication test and the extreme conditions test. In order to guide decision-makers in the different uses of the above system dynamic model, a methodology for the improvement of the AFSC robustness is presented and applied to a case study. As a result, the SC robustness to the defined disruptions is provided. For critical disruptions, protective actions are defined. Finally, the model is re-run to evaluate the impact of these proactive strategies on the AFSC in order to finally select the most beneficial for improving its robustness.