dc.creatorSantos Lima, Fabiana
dc.creatorOliveira, Daniel de
dc.creatorBuss Gonçalves, Mirian
dc.creatorAltimari Samed, Márcia Marcondes
dc.date2014-10-10T04:18:43Z
dc.date2014-10-10T04:18:43Z
dc.date2014
dc.date.accessioned2018-04-19T21:10:14Z
dc.date.available2018-04-19T21:10:14Z
dc.identifierJournal of Technology Management & Innovation 9(2): 2014, p. 86-97
dc.identifierhttp://repositorio.uahurtado.cl/handle/11242/4372
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1372119
dc.descriptionIn this paper, we propose a methodology to identify and classify regions by the type and frequency of disasters. The data on the clusters allow you to extract information that can be used in the preparedness phase as well as to identify the relief items needed to meet each cluster. Using this approach, the clusters are formed by using a computing tool that uses as the input the history data of the disasters in the Brazilian state of Santa Catarina, with a specific focus on: windstorms, hail, floods, droughts, landslides, and flash floods. The results show that the knowledge provided by the clustering analysis contributes to the decision making process in the response phase of Humanitarian Logistics (HL).
dc.languageen_US
dc.publisherUniversidad Alberto Hurtado. Facultad de Economía y Negocios
dc.rightsAttribution 3.0 Unported
dc.rightshttp://creativecommons.org/licenses/by/3.0/
dc.subjectHumanitarian Logistics
dc.subjectClusters
dc.subjectNatural Disasters
dc.subjectPreparedness and Response
dc.subjectProcurement of Relief Supplies
dc.titleHumanitarian Logistics: a Clustering Methodology for Assisting Humanitarian Operations
dc.typeArtículos de revistas


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