In the last decades, some global events such as the economic crisis of 2008 and the COVID‐19 emergency of 2020, have generated more attention towards the housing rental market and its capacity to meet several social needs. In order to study the existent demand for houses, then define the interventions on the residential assets to make them more affordable for the most fragile population groups, adequate evaluation tools are required. With reference to the residential property segment of five metropolitan cities located in the Italian territory, the present research is aimed at analyzing the contribution of the most influencing factors on rental prices. In particular, this research refers to the rented properties of the second half of 2019, with a set of variables that represent the intrinsic and extrinsic factors of the local market. The implementation of an automated valuation model allows the determination of the most significant factors and the functional relationships that they have with housing rental fees. The outputs obtained could support the improvement of equitable public housing policies or could guide private investment decisions, such as refurbishment interventions of certain significant factors that could increase the market rental value. This study is the first step in wider research that is currently in progress, which aims to investigate the effects of the existing COVID‐19 pandemic on the residential rental market.

An automatic tool for the determination of housing rental prices: an analysis of the Italian context / Tajani, Francesco; DI LIDDO, Felicia; Ranieri, Rossana; Anelli, Debora. - In: SUSTAINABILITY. - ISSN 2071-1050. - 14(2021). [10.3390/su14010309]

An automatic tool for the determination of housing rental prices: an analysis of the Italian context

Francesco Tajani;Felicia Di Liddo;Rossana Ranieri;Debora Anelli
2021

Abstract

In the last decades, some global events such as the economic crisis of 2008 and the COVID‐19 emergency of 2020, have generated more attention towards the housing rental market and its capacity to meet several social needs. In order to study the existent demand for houses, then define the interventions on the residential assets to make them more affordable for the most fragile population groups, adequate evaluation tools are required. With reference to the residential property segment of five metropolitan cities located in the Italian territory, the present research is aimed at analyzing the contribution of the most influencing factors on rental prices. In particular, this research refers to the rented properties of the second half of 2019, with a set of variables that represent the intrinsic and extrinsic factors of the local market. The implementation of an automated valuation model allows the determination of the most significant factors and the functional relationships that they have with housing rental fees. The outputs obtained could support the improvement of equitable public housing policies or could guide private investment decisions, such as refurbishment interventions of certain significant factors that could increase the market rental value. This study is the first step in wider research that is currently in progress, which aims to investigate the effects of the existing COVID‐19 pandemic on the residential rental market.
2021
rent market; housing prices; automated valuation method; residential properties; Italian residential market
01 Pubblicazione su rivista::01a Articolo in rivista
An automatic tool for the determination of housing rental prices: an analysis of the Italian context / Tajani, Francesco; DI LIDDO, Felicia; Ranieri, Rossana; Anelli, Debora. - In: SUSTAINABILITY. - ISSN 2071-1050. - 14(2021). [10.3390/su14010309]
File allegati a questo prodotto
File Dimensione Formato  
Tajani_Sustainability-rents_2021.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 678.54 kB
Formato Adobe PDF
678.54 kB Adobe PDF

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/11573/1598998
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 5
social impact