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dc.contributor.authorDíaz Curbelo, Alina 
dc.contributor.authorGento Municio, Ángel Manuel 
dc.date.accessioned2025-01-15T13:50:17Z
dc.date.available2025-01-15T13:50:17Z
dc.date.issued2021
dc.identifier.citationDavid de la Fuente, Raúl Pino, Borja Ponte, Rafael Rosillo (eds.). Organizational Engineering in Industry 4.0. ICIEOM 2018. Lecture Notes in Management and Industrial Engineering. 2021, p. 137-148.es
dc.identifier.isbn978-3-030-67707-7es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/73880
dc.descriptionProducción Científicaes
dc.description.abstractThe interdependent nature of supply chain elements and events requires risk systems must be assessed as an interrelated framework to optimize their management and integrate effectively with other decision-making tools in uncertain environments. This research shows a synthesis and analysis of the main qualitative/quantitative methods that have been used in the literature considering the treatment of event dependencies in supply chain risk management in the period 2003– 2018. The results revealed that the integration with disruption analysis tools and artificial intelligence methods are the most common types adopted, with increasing trend and effectiveness of Bayesian and fuzzy theory approaches.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherSpringeres
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses
dc.subject.classificationSupply chaines
dc.subject.classificationRisk assessmentes
dc.subject.classificationDependencyes
dc.subject.classificationQuantitative methodses
dc.titleQuantitative and qualitative models for managing risk interdependencies in supply chaines
dc.typeinfo:eu-repo/semantics/bookPartes
dc.rights.holder© Springer Nature Switzerland AG 2021es
dc.identifier.doi10.1007/978-3030-67708-4_15
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-030-67708-4_15es
dc.identifier.publicationfirstpage137es
dc.identifier.publicationlastpage148es
dc.identifier.publicationtitleOrganizational Engineering in Industry 4.0
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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