Identification and assessment of hidden capacities of urban resilience

Ghouchani, Mahya; Taji, Mohammad; Roshan, Amirhassan Yaghoubi; Chehr, Mohammad Seifi

doi:10.1007/s10668-020-00752-8

Cited by 13 publications

(8 citation statements)

References 35 publications

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“…The increase in the level of openness will have an impact on the urban economic system and reduce the overall resilience of the city. Meanwhile, this paper also explores and finds that influencing factors such as urbanization level, emergency facility level, and industrial structure have positive impacts on the improvement of urban resilience, which is consistent with the findings of Dong et al (2020) [60], Khan et al (2021) [36], and Ghouchani et al (2021) [61]. On this basis, this paper further explores the temporal and spatial heterogeneity of influencing factors on urban resilience.…”

Section: Theoretical Contributionsupporting

confidence: 85%

Evaluation and Factor Analysis for Urban Resilience: A Case Study of Chengdu–Chongqing Urban Agglomeration

Wang

Han

et al. 2022

Buildings

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Resilient cities provide a new operating mechanism for sustainable urban development and can effectively reduce urban disaster losses. Urban resilience has become an important research topic, but few scholars focus on the urban resilience of urban agglomerations in western China. Therefore, this paper takes the Chengdu–Chongqing urban agglomeration of China as the study area and aims to evaluate the resilience level of cities in typical regions of western China. This study uses multiple interdisciplinary methods, such as the entropy weight method, Theil index, and geographically and temporally weighted regression, to evaluate the resilience levels of 16 cities in the region and discuss the influencing factors of regional urban resilience. The results show that the urban resilience of cities in the Chengdu–Chongqing urban agglomeration has evolved from a low to high level. Additionally, there are significant spatial differences in urban resilience in the Chengdu–Chongqing urban agglomeration, and the resilience levels of cities in the east and west of the region are relatively high, while the resilience levels of cities in the south and north are relatively low. Further research found that factors such as administrative level, marketization level, industrial structure, population density, urbanization level, and emergency facility level all have a significant positive impact on the improvement of urban resilience, but this impact has spatial and temporal heterogeneity. Based on the above research results, the strategies have been proposed from the perspective of sustainable urban development to provide a new theoretical support and decision-making reference for improving the resilience level of urban agglomerations in western China.

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Section: Theoretical Contributionsupporting

confidence: 85%

Evaluation and Factor Analysis for Urban Resilience: A Case Study of Chengdu–Chongqing Urban Agglomeration

Wang

Han

et al. 2022

Buildings

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“…Therefore, industrial agglomeration is an important way to realize overall technological progress in an industry. Agglomeration stimulates the generation of technological innovation, enhancing the ability of the relevant industrial system to resist shocks and the ability to move toward a new growth model (Ghouchani et al, 2021 ; Rocchetta & Mina, 2019 ). In addition, studies have explored the relationship between industrial agglomeration and economic resilience from other perspectives.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China

Zheng

Zhu

et al. 2022

Environ Dev Sustain

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The coordinated development of industrial agglomeration and economic resilience can drive regional economic advantages; this type of development has become a catalyst for sustainable growth and high-quality development of the economy in China. This study applied models, including the coupling coordination degree, spatial autocorrelation, and Tobit, to explore the heterogeneous characteristics of the coupling of China’s industrial agglomeration and regional economic resilience from 2005 to 2019. Additionally, by applying the perspectives of economic and geographic location, indicators were selected to analyze the associated influencing factors, including industrial externalities, new economic geographies, economic policy factors, and other aspects. We found that the overall coupling between industrial agglomeration and economic resilience increased over the study period, but with only a moderate level of coordination. Provinces with high, moderate, and low levels of coordination eventually emerged along a strip-like alternating pattern in space. The dependence increased with an increase in space, but was not significant, and there was a lack of benign interaction between the regions. With respect to interactivity between locations, the interaction of the east and the coast was the most active. There were lower levels of interaction between the west and inland regions. This further confirmed the significant temporal and spatial heterogeneity of the coupling. Environmental pollution, market consumption, the quality of space, and technological support significantly promoted the coupling; opening to the outside world did not. Specifically, with respect to economic location, market consumption and spatial quality had a significant positive effect on the eastern coupling. The center and west regions were significantly affected by economic density and market consumption, and the northeast region was affected by spatial quality and capital intensity. Concerning geographical location, market and technological forces strongly promoted interactions in both the coast and inland regions. The study found that both the government and the market need better guidance to effectively engage with and shape industrial agglomeration and economic resilience in a scientific, reasonable, localized, and distinctive manner.

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“…is section reviews the literature related to urban resilience. Many researchers have developed some indicators, frameworks, and conceptual models to quantify resilience analysis [3,[28][29][30][31][32][33][34][35]. Our first task is to establish a suitable evaluation framework to measure the resilience of cities and then, by collecting and sorting out relevant data sets, to create an urban resilience knowledge system.…”

Section: Description Of the Evaluation Framework And Attributesmentioning

confidence: 99%

“…Ratio of local police officers to the population (unit: %) Ghouchani et al [34] Ratio of firefighters to population (CC7)…”

Section: Stability Of Water Supply (Cc5)mentioning

confidence: 99%

“…Zheng et al [30]; Okada [35]; Ghouchani et al [34] Environmental conditions (GC) A trapezoidal fuzzy number can be denoted as E � (e 1 , e 2 , e 3 , e 4 ), where e 1 < e 2 < e 3 < e 4 . Suppose there are two trapezoidal fuzzy numbers P � (p 1 , p 2 , p 3 , p 4 ) and Q � (q 1 , q 2 , q 3 , q 4 ), and θ is a positive constant number.…”

Section: E Definition and Operation Laws Of Trapezoidal Fuzzymentioning

confidence: 99%

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A Hybrid Z-Based MADM Model for the Evaluation of Urban Resilience

Huang

2021

Mathematical Problems in Engineering

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Natural disasters and man-made incidents have many negative impacts on major cities, including casualties, economic losses, disruption of social order, and environmental contamination. Cities need to be resilient in order to protect people’s lives and property. Although research on urban resilience has been rapidly emerging in recent years, there are still some research gaps. The interplay of attributes for assessing urban resilience has not been explored, and the Multiple Attribute Decision Making- (MADM-) based framework for evaluating urban resilience is rarely studied. Therefore, this study proposes a novel model to evaluate urban resilience, the Z number-based Decision-Making Trial, and Evaluation Laboratory (Z-DEMATEL), to identify the mutual influential relationships and the weights of the attributes. In addition, the Z number-based Reference Ideal Method (Z-RIM) is used to determine the resilience capacity of cities and to suggest improvements for decision makers to develop appropriate strategies. In this study, we not only use trapezoidal fuzzy numbers to reflect the uncertainty of information but also measure the reliability/confidence of experts in the assessment. The integrated methodology is presented for the first time in this study, and we use the firmness data of six major metropolitan cities in Taiwan as an example of model demonstration. The results of the study show that population density, value of business activity, healthcare facilities, electricity supply, and number of business registrations are the most important attributes influencing the resilience of cities. Taipei City and Taichung City are the two major cities with better resilience in Taiwan based on the analysis of this study.

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Identification and assessment of hidden capacities of urban resilience

Cited by 13 publications

References 35 publications

Evaluation and Factor Analysis for Urban Resilience: A Case Study of Chengdu–Chongqing Urban Agglomeration

Evaluation and Factor Analysis for Urban Resilience: A Case Study of Chengdu–Chongqing Urban Agglomeration

Spatial–temporal heterogeneity and influencing factors of the coupling between industrial agglomeration and regional economic resilience in China

A Hybrid Z-Based MADM Model for the Evaluation of Urban Resilience

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