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A hybrid intelligent model for assessment of critical success factors in high-risk emergency system

  • Yuzhen Han
  • Yong DengEmail author
Original Research

Abstract

High-risk emergency systems are emerging as a new generation technology to prevent disasters. Latest research points out that these systems could protect properties and lives in an efficient way. Limited to the sources, the feasible way to improve the performance of the system is to identify critical success factors (CSFs) and then optimize them. In this paper, a multi-criteria decision-making (MCDM) approach integrating Affinity Diagram, Decision Making Trial and Evaluation Laboratory (DEMATEL), fuzzy cognitive map (FCM) and Dempster–Shafer evidence theory (evidence theory) is proposed to identify critical success factors in high-risk emergency system. The DEMATEL and FCM are initially combined to tackle the decision-making problem in theory and practice. This model has ability to fuse technical, economic, political and social attributes. The proposed method is applied to select CSFs for Chongqing city.

Keywords

DEMATEL Fuzzy cognitive map Dempster–Shafer evidence theory Critical success factors High-risk emergency system Multi-criteria decision making 

Notes

Acknowledgements

The authors are grateful to anonymous reviewers for their useful comments and suggestions on improving this paper.

Funding

The work is partially supported by National Natural Science Foundation of China (Grant Nos. 61573290, 61503237).

Compliance with ethical standards

Conflict of interest

Yuzhen Han declares that he has no conflict of interest. Yong Deng declares that he has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Fundamental and Frontier ScienceUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Computer and Information ScienceSouthwest UniversityChongqingChina

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