Capitalisation rates and 'real estate semantic chains': an application of clustering analysis
| Autor: | Salvatore Giuffrida, A. Valenti, G. Ferluga |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
old towns
clustering analysis Information Systems and Management Computer science Real estate imperfect real estate markets computer.software_genre Management Information Systems hierarchical aggregative algorithm Cluster analysis Speculation Industrial organization Valuation (finance) old towns urban renovation imperfect real estate markets mass-appraisals financial speculative approach theory of capital semiotic approach semantic chains capitalisation rate data mining clustering analysis hierarchical aggregative algorithm capitalisation rate semantic chains Local property theory of capital Subsidy urban renovation mass-appraisals data mining financial speculative approach Complete linkage semiotic approach Capital asset Data mining Statistics Probability and Uncertainty computer |
| Zdroj: | International Journal of Business Intelligence and Data Mining. 10:174 |
| ISSN: | 1743-8195 1743-8187 |
| DOI: | 10.1504/ijbidm.2015.069271 |
| Popis: | Ortigia, the historic centre of Syracuse, is a complex urban entity characterised by high outer homogeneity and inner heterogeneity. The evolution of its real estate market during the last decade is somehow related to the global property market one. In addition its events are connected with the evolution of the exploiting policies still ongoing. The critical observations of its features aim at providing tools able to support the decisions about subsidies and local property taxes. This study continues the observations we have carried out for five years, this time involving clustering analysis, a data mining technique able to recognise different submarkets, and suitable to make the valuation pattern fit to the different market areas. For each of the latter significant characteristics have been recognised with reference to the 'monetary declination' of these particular capital assets. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|