Although the presence of an urban green areas seems to be an important factor in housing decisions, there are few empirical research on the incidence of different types of urban green spaces on housing prices. With reference to a study sample of apartments located in the Flaminio district of the city of Rome (Italy), an innovative data-driven technique has been implemented. In this way, it was possible to identify, among the main explanatory variables selected by the model as the most influential in real estate price formation phenomena, those relating to green areas and analyzing the marginal contribution of each of them on selling prices. The implemented methodology has allowed to obtain a model characterized by high statistical reliability, by a simplicity and high coherence in the empirical interpretation of the functional relationships between the influencing factors selected and the housing prices. The results clearly indicate that green space is not a homogeneous environmental amenity, rather it is a series of distinct elements that has a different impact on housing prices.

Incidence of Different Types of Urban Green Spaces on Property Prices. A Case Study in the Flaminio District of Rome (Italy) / Morano, Pierluigi; Guarini, Maria Rosaria; Tajani, Francesco; Di Liddo, Felicia; Anelli, Debora. - 11622:(2019), pp. 23-34. (Intervento presentato al convegno 19th International Conference on Computational Science and Applications (ICCSA 2019) tenutosi a Saint Petersburg, Russia,) [10.1007/978-3-030-24305-0_3].

Incidence of Different Types of Urban Green Spaces on Property Prices. A Case Study in the Flaminio District of Rome (Italy)

Morano, Pierluigi
;
Guarini, Maria Rosaria;Tajani, Francesco;Di Liddo, Felicia;ANELLI, DEBORA
2019

Abstract

Although the presence of an urban green areas seems to be an important factor in housing decisions, there are few empirical research on the incidence of different types of urban green spaces on housing prices. With reference to a study sample of apartments located in the Flaminio district of the city of Rome (Italy), an innovative data-driven technique has been implemented. In this way, it was possible to identify, among the main explanatory variables selected by the model as the most influential in real estate price formation phenomena, those relating to green areas and analyzing the marginal contribution of each of them on selling prices. The implemented methodology has allowed to obtain a model characterized by high statistical reliability, by a simplicity and high coherence in the empirical interpretation of the functional relationships between the influencing factors selected and the housing prices. The results clearly indicate that green space is not a homogeneous environmental amenity, rather it is a series of distinct elements that has a different impact on housing prices.
2019
19th International Conference on Computational Science and Applications (ICCSA 2019)
housing prices; urban green spaces; private green areas; genetic algorithm
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Incidence of Different Types of Urban Green Spaces on Property Prices. A Case Study in the Flaminio District of Rome (Italy) / Morano, Pierluigi; Guarini, Maria Rosaria; Tajani, Francesco; Di Liddo, Felicia; Anelli, Debora. - 11622:(2019), pp. 23-34. (Intervento presentato al convegno 19th International Conference on Computational Science and Applications (ICCSA 2019) tenutosi a Saint Petersburg, Russia,) [10.1007/978-3-030-24305-0_3].
File allegati a questo prodotto
File Dimensione Formato  
Guarini M.R._Types-Urban-Green_2019.pdf

solo gestori archivio

Note: https://www.springer.com/gp/book/9783030243043
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.91 MB
Formato Adobe PDF
2.91 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1299855
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 10
social impact