Risk assessment model using conditional probability and simulation: case study in a piped gas supply chain in Brazil

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorFederal University of Paraíba-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorSilva, Liane Marcia Freitas [UNESP]-
Autor(es): dc.creatorde Oliveira, Ana Camila Rodrigues-
Autor(es): dc.creatorLeite, Maria Silene Alexandre-
Autor(es): dc.creatorMarins, Fernando A. S. [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:30:25Z-
Data de disponibilização: dc.date.available2022-02-22T00:30:25Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1080/00207543.2020.1744764-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/200379-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/200379-
Descrição: dc.descriptionThe objective of this article is to present a proposed application for systematic risk assessment considering the dependence between risks. The proposal relies on a systematic literature review (SLR) as the initial phase, in which the risk classes, management phases and the tools that can be applied to the risk assessment are identified, considering the dependence between them. For this, the system adopted includes the identification and later evaluation of the risks. The evaluation involves the analytic network process (ANP), Monte Carlo Simulation and conditional probability by means of Bayes’ theorem. The identification and evaluation of the risks were applied to two links of a piped gas supply chain in Brazil, identified as company X and Y, where six specialists were interviewed in each company in the managerial areas. The ANP indicted that the most critical risk in the links is the demand risk. From this, it was possible through Monte Carlo Simulation to identify the probability of occurrence of events with connection to demand risk: demand (X) / demand risk (Y), with probability of 10%; price risk (X) / demand risk (Y), with probability of 0.64%; and risk of supply (Y) / demand risk (X), with a probability of 0%. This indicates that the highest risk is the risk of demand of firm Y, and therefore mitigation strategies should focus on this risk, as it represents the true cause of supply chain vulnerability, generating risk with the highest probability.-
Descrição: dc.descriptionDepartment of Production Engineering Federal University of Paraíba-
Descrição: dc.descriptionDepartment of Production Engineering University Estadual Paulista–UNESP School of Guaratingueta- EGF Engineering-
Descrição: dc.descriptionDepartment of Production Engineering University Estadual Paulista–UNESP School of Guaratingueta- EGF Engineering-
Idioma: dc.languageen-
Relação: dc.relationInternational Journal of Production Research-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectanalytical network process (ANP)-
Palavras-chave: dc.subjectMonte Carlo simulation-
Palavras-chave: dc.subjectrisk assessment-
Palavras-chave: dc.subjectrisk management-
Palavras-chave: dc.subjectsupply chain risk management (SCRM)-
Título: dc.titleRisk assessment model using conditional probability and simulation: case study in a piped gas supply chain in Brazil-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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