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

• Published in: Land use policy Vol. 128; p. 106595
• Main Authors: Anelli, Debora, Tajani, Francesco
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2023
• Subjects: decision making; decision support systems; ex ante analysis; geographic information systems; Italy; land policy; Multi-criteria analysis; Real estate risk; risk; Risk assessment; Risk map; Spatial decision support system; sustainable development; Synthetic risk index; Urban redevelopment; Italy; Real estate risk; Synthetic risk index; Urban redevelopment; Multi-criteria analysis; Risk assessment; Spatial decision support system; Risk map
• ISSN: 0264-8377; 1873-5754; 1873-5754
• DOI: 10.1016/j.landusepol.2023.106595

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 sub-municipal 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. •Innovative ex-ante real estate risk evaluation model.•Structured framework for creating a Spatial Real Estate Risk Index.•Public-Private Partnerships’ decisions support system.•Integrated methodological approach for quantitative and qualitative real estate risk assessment.•Creation of a risk map able to represent the spatial distribution of the investment’s real estate risk at the sub-municipal territorial scale.•Possibility of immediately recognize the riskiest and least risky sub-municipal areas within the city analyzed.•Main practical implications: the ranking of the urban areas according to the risk levels and the determination of the “base risk” for the private entrepreneur involved into PPP urban redevelopment initiatives.•Structured procedure very flexible as it can work for different purposes of ranking, comparing or analyzing the real estate risk issues.