Analysis of PCA with georeferenced data. An application in tourism industry
Fil: Luna, Laura Isabel. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina.
| Main Author: | |
|---|---|
| Format: | conferenceObject |
| Language: | eng |
| Published: |
2023
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/11086/549688 |
| _version_ | 1806012296522104832 |
|---|---|
| author | Luna, Laura Isabel |
| author_facet | Luna, Laura Isabel |
| author_sort | Luna, Laura Isabel |
| collection | Repositorio Digital Universitario |
| description | Fil: Luna, Laura Isabel. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina. |
| format | conferenceObject |
| id | rdu-unc.549688 |
| institution | Universidad Nacional de Cordoba |
| language | eng |
| publishDate | 2023 |
| record_format | dspace |
| spelling | rdu-unc.5496882024-07-10T12:05:10Z Analysis of PCA with georeferenced data. An application in tourism industry Luna, Laura Isabel Industry tourism Spatial multivariate annalysis Fuzzy k-means Fil: Luna, Laura Isabel. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina. The spatial analysis of the tourism characteristic activities allows us to generate information about the structure of tourism industry, which is necessary for decision making. In this work, toursim characteristic activities in the departments of Córdoba were mapped. The methodological innovation lies in the generation of statistics for multidimensional spatial data. Multivariate methods with and without spatial restrictions were studied and compared in their performance in the application context. The comparison showed that the spatial principal components analysis (MULTISPATI-PCA) yielded a higher degree of spatial structuring of the components that summarize tourism activities than principal components analysis (PCA). The maps of the summarized variables showed a higher level of structure with MULTISPATI-PCA. Departments were classified according to the participation of tourism activities in the value added of tourism using the spatial principal components obtained as input of the cluster fuzzy k-means analysis. Finally, a mapping was performed based on the participation of the tourism value added in the gross regional product of the different departments and the variations in the participation of the different activities that make up the aggregate was analyzed for the period 2001-2014. Fil: Luna, Laura Isabel. Universidad Nacional de Córdoba. Facultad de Ciencias Económicas; Argentina. Economía, Econometría 2023-10-26T18:09:09Z 2023-10-26T18:09:09Z 2019-09 conferenceObject 978-950-34-1854-3 http://hdl.handle.net/11086/549688 eng Licencia Creative Commons Atribución – No Comercial – Sin Obra Derivada 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ Impreso |
| spellingShingle | Industry tourism Spatial multivariate annalysis Fuzzy k-means Luna, Laura Isabel Analysis of PCA with georeferenced data. An application in tourism industry |
| title | Analysis of PCA with georeferenced data. An application in tourism industry |
| title_full | Analysis of PCA with georeferenced data. An application in tourism industry |
| title_fullStr | Analysis of PCA with georeferenced data. An application in tourism industry |
| title_full_unstemmed | Analysis of PCA with georeferenced data. An application in tourism industry |
| title_short | Analysis of PCA with georeferenced data. An application in tourism industry |
| title_sort | analysis of pca with georeferenced data an application in tourism industry |
| topic | Industry tourism Spatial multivariate annalysis Fuzzy k-means |
| url | http://hdl.handle.net/11086/549688 |
| work_keys_str_mv | AT lunalauraisabel analysisofpcawithgeoreferenceddataanapplicationintourismindustry |