Vulnerability analysis of urban old residential areas for stock renewal: an unascertained measure theory approach

The renovation of urban old residential areas (UORA) is a crucial measure in urban stock renewal for improving the quality of residents’ lives. Scientifically understanding the multidimensional vulnerability of UORA is a prerequisite for implementing stock renewal. However, existing vulnerability assessment methods for UORA suffer from limitations such as subjective weight assignment, and insufficient handling of uncertain information, leading to inadequate support for precise renewal decisions. To address these gaps, this study proposes a novel multidimensional vulnerability evaluation framework. A vulnerability evaluation index system is constructed from physical space, infrastructure, functional adaptation, ecological environment, and social governance. A comprehensive evaluation model is established by integrating the combined entropy weight method and the unascertained measure theory. This methodological innovation enhances the objectivity of weight determination while effectively addressing unstructured data and uncertain factors in vulnerability assessment. The empirical results show that the vulnerability evaluation results of the six projects are clearly polarised. High-risk clusters need to prioritise the initiation of engineering interventions and social governance reconstruction; for medium-risk projects, dynamic monitoring and adaptive management should be strengthened. This study provides a priority standard and scientific support for renewal decisions and promotes the transformation of vulnerability assessment from a single diagnosis to a systematic governance paradigm.​.

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Publication Details

Journal
Ain Shams Engineering Journal
Published
2026-01-21
DOI
https://doi.org/10.1016/j.asej.2026.104003
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Vulnerability analysis of urban old residential areas for stock renewal: an unascertained measure theory approach

Ping Guo, Jiwei Zhu
Ain Shams Engineering Journal
Flood Risk Assessment and Management
article

Vulnerability analysis of urban old residential areas for stock renewal: an unascertained measure theory approach

Ping Guo, Jiwei Zhu
article en

Abstract

The renovation of urban old residential areas (UORA) is a crucial measure in urban stock renewal for improving the quality of residents’ lives. Scientifically understanding the multidimensional vulnerability of UORA is a prerequisite for implementing stock renewal. However, existing vulnerability assessment methods for UORA suffer from limitations such as subjective weight assignment, and insufficient handling of uncertain information, leading to inadequate support for precise renewal decisions. To address these gaps, this study proposes a novel multidimensional vulnerability evaluation framework. A vulnerability evaluation index system is constructed from physical space, infrastructure, functional adaptation, ecological environment, and social governance. A comprehensive evaluation model is established by integrating the combined entropy weight method and the unascertained measure theory. This methodological innovation enhances the objectivity of weight determination while effectively addressing unstructured data and uncertain factors in vulnerability assessment. The empirical results show that the vulnerability evaluation results of the six projects are clearly polarised. High-risk clusters need to prioritise the initiation of engineering interventions and social governance reconstruction; for medium-risk projects, dynamic monitoring and adaptive management should be strengthened. This study provides a priority standard and scientific support for renewal decisions and promotes the transformation of vulnerability assessment from a single diagnosis to a systematic governance paradigm.​.

Ain Shams Engineering JournalVol. 17(2)
Xi'an University of Architecture and Technology (CN)
Openalex Percentile: Top 87%
Flood Risk Assessment and Management
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