The real estate redevelopment process is an important route for achieving the sustainable development goals established worldwide, but at the same time it represents a complex and not very transparent decision-making issue for the public and private subjects involved. In particular, for the private entrepreneurs it is generally considered more risky than new construction, therefore it requires a careful evaluation for avoiding losses. Most of the existent risk assessment tools provide for the analysis at the aggregated scales or require knowledge of many financial data of the project which are often not yet known in an ex-ante evaluation condition. Aim of the work is to define a structured framework for creating a Spatial Real Estate Risk Index (ISRR) through a spatial decision support system based on an innovative model that allows public and private subjects to carry out an effective ex-ante risk assessment at the sub-municipal territorial scale for public-private partnerships (PPP) risks. The proposed model adopts the flexibility of the Analytic Hierarchy Process multicriteria technique for managing qualitative and quantitative real estate data, the capability of indicators system to reduce the complexity of the real estate risk issues and the sleight of the Geographic Information System to clearly show the spatial distribution of the real estate risk. The ISRR is a territorial synthetic index that represents the “base risk”, i.e. the risk level that is expressed by the different features that characterize the demand and supply of the several urban areas within the city at the time of the evaluation. In order to test the usefulness of the proposed model, the application to the city of Rome (Italy) is described. The obtained results highlight the immediate ability to recognize the riskiest urban areas located on the northern and eastern boundaries of the city. The innovative contribution of the work is mainly represented by the analysis of the real estate risk carried out at the submunicipal scale by using both quantitative and qualitative real estate data, therefore the proposed structured framework for creating the ISRR allows to immediately recognize the riskiest and least risky sub-municipal areas through an adequate risk map.

Spatial decision support systems for effective ex-ante risk evaluation: An innovative model for improving the real estate redevelopment processes / Anelli, Debora; Tajani, Francesco. - In: LAND USE POLICY. - ISSN 0264-8377. - 128(2023). [10.1016/j.landusepol.2023.106595]

Spatial decision support systems for effective ex-ante risk evaluation: An innovative model for improving the real estate redevelopment processes

Francesco Tajani
2023

Abstract

The real estate redevelopment process is an important route for achieving the sustainable development goals established worldwide, but at the same time it represents a complex and not very transparent decision-making issue for the public and private subjects involved. In particular, for the private entrepreneurs it is generally considered more risky than new construction, therefore it requires a careful evaluation for avoiding losses. Most of the existent risk assessment tools provide for the analysis at the aggregated scales or require knowledge of many financial data of the project which are often not yet known in an ex-ante evaluation condition. Aim of the work is to define a structured framework for creating a Spatial Real Estate Risk Index (ISRR) through a spatial decision support system based on an innovative model that allows public and private subjects to carry out an effective ex-ante risk assessment at the sub-municipal territorial scale for public-private partnerships (PPP) risks. The proposed model adopts the flexibility of the Analytic Hierarchy Process multicriteria technique for managing qualitative and quantitative real estate data, the capability of indicators system to reduce the complexity of the real estate risk issues and the sleight of the Geographic Information System to clearly show the spatial distribution of the real estate risk. The ISRR is a territorial synthetic index that represents the “base risk”, i.e. the risk level that is expressed by the different features that characterize the demand and supply of the several urban areas within the city at the time of the evaluation. In order to test the usefulness of the proposed model, the application to the city of Rome (Italy) is described. The obtained results highlight the immediate ability to recognize the riskiest urban areas located on the northern and eastern boundaries of the city. The innovative contribution of the work is mainly represented by the analysis of the real estate risk carried out at the submunicipal scale by using both quantitative and qualitative real estate data, therefore the proposed structured framework for creating the ISRR allows to immediately recognize the riskiest and least risky sub-municipal areas through an adequate risk map.
2023
Risk assessment; Synthetic risk index; Multi-criteria analysis; Spatial decision support system; Risk map; Real estate risk; Urban redevelopment
01 Pubblicazione su rivista::01a Articolo in rivista
Spatial decision support systems for effective ex-ante risk evaluation: An innovative model for improving the real estate redevelopment processes / Anelli, Debora; Tajani, Francesco. - In: LAND USE POLICY. - ISSN 0264-8377. - 128(2023). [10.1016/j.landusepol.2023.106595]
File allegati a questo prodotto
File Dimensione Formato  
Tajani_Ex ante-risk-evaluation_2023.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 6.2 MB
Formato Adobe PDF
6.2 MB 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/11573/1672292
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 6
social impact