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

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  • Chun-Nen Huang
  • Huai-Wei Lo

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.

Suggested Citation

  • Chun-Nen Huang & Huai-Wei Lo, 2021. "A Hybrid Z-Based MADM Model for the Evaluation of Urban Resilience," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-17, September.
  • Handle: RePEc:hin:jnlmpe:9474753
    DOI: 10.1155/2021/9474753
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    Cited by:

    1. Lo, Huai-Wei & Lin, Sheng-Wei, 2023. "Identifying ESG investment key indicators and selecting investment trust companies by using a Z-fuzzy-based decision-making model," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    2. Kuan-Yu Lin & Cheng-Lu Yeng & Yi-Kuei Lin, 2024. "Evaluating Order Allocation Sustainability Using a Novel Framework Involving Z-Number," Mathematics, MDPI, vol. 12(16), pages 1-15, August.

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