MARISMA-BiDa: Gestión y Control del riesgo en Big Data. Caso de Estudio

Rosado, David G.; Moreno, J. C.; Sánchez, Luís Enrique; Olmo, Antonio Santos; Serrano, Manuel Alberca; Fernandez-Medina, E.

doi:10.12804/si9789587844337.03

Cited by 1 publication

(1 citation statement)

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“…[1] propone modelos cuantitativos, como la programación estocástica y la optimización robusta con Big Data para analizar situaciones disruptivas, aunque requieren conocimiento previo de los riesgos. Mientras Rosado, D. et al [2] define un patrón específico (MARISMA-BiDa) para facilitar el análisis de riesgos en entornos Big Data, demostrando su aplicación en un caso de estudio.…”

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Big Data in Risk Management in the Supply Chain: A Systematic Review

Espinoza Cerdan,

Bocanegra Chistama,

Palma Rojas

et al. 2024

goi

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This research article finds out the impact of applying big data concepts to supply chain management. The different types of risks that can affect the supply chain are identified and their impact on business operations is understood. Likewise, the techniques and tools available for the collection, processing and analysis of large volumes of data related to the supply chain are evaluated. The available means in which professionals can apply big data in the supply chain are determined, for the benefit of organizations dedicated to the production of different types of goods. Bases are established to start the investigation of the information, the keywords, the databases from which this information is going to be obtained; Likewise, the objectives, inclusion and exclusion criteria are provided, which make up the search strategy. In conclusion, this study shows a synthesis on the analysis of big data in risk management within the supply chain, emphasizing the impact of these concepts in the supply chain.

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