Disaster risk evaluation using factor analysis: a case study of Chinese regions

  • Ning ChenEmail author
  • Lu Chen
  • Chaosheng Tang
  • Zhengjiang Wu
  • An Chen
Original Paper


Regional risk to natural disasters is a critical multi-criteria decision-making (MCDM) problem in the literature due to the complicated and usually conflicting evaluation index system. Although a variety of MCDM methods can be applied to deal with the problem, the prior study primarily focused on the ranking of alternatives with little investigation on the influence of indicators. In this paper, an integrated approach is proposed by combining factor analysis and MCDM techniques to evaluate the thirty-one Chinese regions in terms of twenty-eight indicators. The advantage of factor analysis is demonstrated in extracting the dominant factors in an interpretable manner. Two commonly used MCDM techniques, namely TOPSIS and VIKOR, are then employed to evaluate the comprehensive risk of regions to natural hazards. The proposed approach not only provides the ranking of regions but also reveals the influence of indicators on the regional risk.


Regional disaster risk evaluation Multi-criteria decision-making Factor analysis Ranking 



This work was supported by national funds through the Beijing National Science Foundation (9182017), the Cooperation Project of the Development Research Center of China Earthquake Administration (Y802701901), and the Cooperation Project of Beijing Municipal Institute of Labor Protection (PXM2018_178304_000010). I hereby express gratitude to Ms. Xiaohui Yao for her contribution on data collection and preprocessing.

Supplementary material

11069_2019_3742_MOESM1_ESM.xlsx (15 kb)
Supplementary material 1 (xlsx 15 KB)


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyHenan Polytechnic UniversityJiaozuoPeople’s Republic of China
  2. 2.School of LogisticsBeijing Wuzi UniversityBeijingPeople’s Republic of China
  3. 3.Institutes of Science and DevelopmentChinese Academy of SciencesBeijingPeople’s Republic of China
  4. 4.University of Chinese Academy of SciencesBeijingPeople’s Republic of China

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