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Developing indicators for sustainable urban regeneration in historic urban areas: Delphi method and Analytic Hierarchy Process (AHP).
- Source :
- Sustainable Cities & Society; Dec2023, Vol. 99, pN.PAG-N.PAG, 1p
- Publication Year :
- 2023
-
Abstract
- • A new decision-support model for sustainability assessment of urban regeneration. • The indicator-based model integrates social, economic, environmental and governance aspects. • Social aspects contributed the most to the overall sustainability weighting across the four dimensions. • Building and land use were found to be the most important of the 17 evaluation categories. This paper presents a comprehensive evaluation model comprising indicators spanning four dimensions: social, economic, environmental, and governance. Extensive indicators were gathered from the literature and subsequently subjected to a rigorous screening, validation, and finalization process by a panel of 25 international experts through a Delphi survey. The relative weights assigned to each indicator were determined utilizing the Analytic Hierarchy Process (AHP). The findings reveal that the social dimension carries the greatest significance in achieving sustainable urban renewal (SUR), closely followed by the environmental dimension. In terms of assessment categories, the highest priority and weight (0.1186) were attributed to "building and land use," while "economic viability" (weight=0.1049), "policymaking" (weight=0.0982), "community involvement" (weight=0.0882), and "housing provision" (weight=0.850) were also identified as significant areas. The paper emphasizes that these proposed indicators can serve as valuable tools to inform the review and enhancement of urban planning guidelines and policies at the local, state, and national levels, fostering sustainable urban regeneration. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22106707
- Volume :
- 99
- Database :
- Supplemental Index
- Journal :
- Sustainable Cities & Society
- Publication Type :
- Academic Journal
- Accession number :
- 173120221
- Full Text :
- https://doi.org/10.1016/j.scs.2023.104990