| Journal: | Journal of technology management & innovation |
| Database: | CLASE |
| System number: | 000534580 |
| ISSN: | 0718-2724 |
| Authors: | Santos Lima, Fabiana1 Oliveira, Daniel de1 Goncalves, Mirian Buss1 Samed, Marcia Marcondes Altimari2 |
| Institutions: | 1Universidade Federal de Santa Catarina, Programa de Pos-Graduacao em Engenharia de Producao, Florianopolis, Santa Catarina. Brasil 2Universidade Estadual de Maringa, Departamento de Engenharia de Producao, Maringa, Parana. Brasil |
| Year: | 2014 |
| Season: | Jul |
| Volumen: | 9 |
| Number: | 2 |
| Pages: | 86-97 |
| Country: | Chile |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Analítico, descriptivo |
| English abstract | In 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) |
| Disciplines: | Administración y contaduría |
| Keyword: | Planeación, Dirección y control, Logistica humanitaria, Agrupaciones, Desastres naturales, Preparación y respuesta, Adquisición de suministros de socorro |
| Keyword: | Planning, Management, Humanitarian logistics, Clusters, Natural disasters, Preparedness and response, Procurement of relief supplies |
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