Analytical Decision Support Systems for Sustainable Urban Regeneration

The rapid urbanization of contemporary cities represents one of the most complex challenges of the 21st century, with profound implications for the environmental, social, and economic sustainability of territories. In this context, urban regeneration emerges as a strategic approach to territorial transformation. The complexity of urban dynamics requires the adoption of innovative paradigms and systemic approaches capable of guiding decision-making processes toward eco-sustainable and resilient solutions. This research develops advanced decision support tools for urban regeneration, using the city of Potenza (Italy) as a case study. The main objective is to identify key indicators to evaluate the effectiveness of urban regeneration interventions in advance (ex-ante). The methodology develops a composite economic-financial risk index capable of providing an accurate picture of existing conditions while adapting to the territorial specificities of the analyzed area. This index, which uses the Analytic Hierarchy Process (AHP) technique to integrate elementary economic-financial indicators in order to assess the sustainability level of urban redevelopment projects, is able to synthesize complex economic variables into a single parameter of immediate comprehension, strategically guiding investments toward a sustainable urban development model. The analysis of results highlights a peculiar territorial configuration: semi-central areas present the greatest criticalities, while there is a progressive decrease in risk both toward the central core and toward peripheral and extra-urban areas. The study represents a significant methodological contribution to future urban regeneration initiatives at the local level, promoting an integrated vision of sustainable urban development for the benefit of current and future generations.

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Publication Details

Journal
Real Estate
Published
2025-06-27
DOI
https://doi.org/10.3390/realestate2030008
Citations
1
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
1.01
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article

Analytical Decision Support Systems for Sustainable Urban Regeneration

Francesco Paolo Del Giudice, Francesco Tajani, Vincenzo Del Giudice, Daniela Tavano et al.
1 citations
Real Estate
Traffic Prediction and Management Techniques
1.01
article

Analytical Decision Support Systems for Sustainable Urban Regeneration

Francesco Paolo Del Giudice, Francesco Tajani, Vincenzo Del Giudice, Daniela Tavano, Giuseppe Cerullo, Benedetto Manganelli
article en
1 citations

Abstract

The rapid urbanization of contemporary cities represents one of the most complex challenges of the 21st century, with profound implications for the environmental, social, and economic sustainability of territories. In this context, urban regeneration emerges as a strategic approach to territorial transformation. The complexity of urban dynamics requires the adoption of innovative paradigms and systemic approaches capable of guiding decision-making processes toward eco-sustainable and resilient solutions. This research develops advanced decision support tools for urban regeneration, using the city of Potenza (Italy) as a case study. The main objective is to identify key indicators to evaluate the effectiveness of urban regeneration interventions in advance (ex-ante). The methodology develops a composite economic-financial risk index capable of providing an accurate picture of existing conditions while adapting to the territorial specificities of the analyzed area. This index, which uses the Analytic Hierarchy Process (AHP) technique to integrate elementary economic-financial indicators in order to assess the sustainability level of urban redevelopment projects, is able to synthesize complex economic variables into a single parameter of immediate comprehension, strategically guiding investments toward a sustainable urban development model. The analysis of results highlights a peculiar territorial configuration: semi-central areas present the greatest criticalities, while there is a progressive decrease in risk both toward the central core and toward peripheral and extra-urban areas. The study represents a significant methodological contribution to future urban regeneration initiatives at the local level, promoting an integrated vision of sustainable urban development for the benefit of current and future generations.

Real EstateVol. 2(3)
University of Basilicata (IT), University of Calabria (IT), University of Naples Federico II (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 23%
Traffic Prediction and Management Techniques
1.01
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