Abstract

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.

Highlights

  • Many disasters caused by extreme weather and human factors negatively affect human life, and this situation is becoming more and more frequent and serious

  • Erefore, in order to fill this research gap, this paper proposes a novel MADM model that combines Z-DEMATEL and Z number-based Reference Ideal Method (Z-Reference Ideal Method (RIM)) to evaluate urban resilience. e proposed modified Z-DEMATEL extends the study of Hsu et al [26] by using trapezoidal fuzzy numbers instead of the general triangular fuzzy numbers in assessing the mutually influential relationships between attributes

  • The evaluation framework constructed with the MADM concept has not yet been fully studied. is study establishes the initial evaluation attributes suitable for assessing urban resilience in Taiwan based on relevant academic literature and opinions from disaster prevention-related ministries and selects relatively important attributes to be included in the evaluation system to reflect the characteristics and connotations of urban resilience. e main framework consists of four dimensions, namely, social infrastructure and community connectivity (SI), contingency capacity (CC), economic strength (ES), and environmental conditions (GC)

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Summary

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

Received 10 August 2021; Revised 13 September 2021; Accepted 15 September 2021; Published 29 September 2021. E 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. Erefore, 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. E 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. E 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

Introduction
Preliminaries
Findings
Illustration of a Real Case

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