Toward smart cities: analysis of critical factors of new disaster risks in smart cities using a fuzzy DANP-ISM method

The transition from traditional cities to smart cities is not only reflected in the optimisation and upgrading of urban infrastructure public services but also in the expansion and intensification of new disaster risks. This study first reviewed the related work on disaster risks of smart cities and thereby constructed an indicator framework of new disaster risk influencing factors for smart cities. Then, a fuzzy DANP-ISM method was developed to analyse the interactions and prioritise these factors. The results revealed the critical factors of new disaster risks in smart cities, including online mass incidents, cyberterrorism, technology ethics, information infrastructure, physical infrastructure, information overcollection, cyber-attacks and information leakage. Among them, information infrastructure and physical infrastructure were the primary influencing factors, with the other factors being influenced by them. Furthermore, major challenges of new disaster risk management in smart cities are discussed in this paper, and corresponding strategies are provided. This study not only enriches the risk studies of smart cities but also provides important theoretical and methodological references for emergency management of smart cities.

Authors

Institutions

Publication Details

Journal
Humanities and Social Sciences Communications
Published
2026-01-29
DOI
https://doi.org/10.1057/s41599-026-06555-y
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Toward smart cities: analysis of critical factors of new disaster risks in smart cities using a fuzzy DANP-ISM method

Xiao Gu, Shanshan Li, Yanqing Wang
Humanities and Social Sciences Communications
Smart Cities and Technologies
article

Toward smart cities: analysis of critical factors of new disaster risks in smart cities using a fuzzy DANP-ISM method

Xiao Gu, Shanshan Li, Yanqing Wang
article en

Abstract

The transition from traditional cities to smart cities is not only reflected in the optimisation and upgrading of urban infrastructure public services but also in the expansion and intensification of new disaster risks. This study first reviewed the related work on disaster risks of smart cities and thereby constructed an indicator framework of new disaster risk influencing factors for smart cities. Then, a fuzzy DANP-ISM method was developed to analyse the interactions and prioritise these factors. The results revealed the critical factors of new disaster risks in smart cities, including online mass incidents, cyberterrorism, technology ethics, information infrastructure, physical infrastructure, information overcollection, cyber-attacks and information leakage. Among them, information infrastructure and physical infrastructure were the primary influencing factors, with the other factors being influenced by them. Furthermore, major challenges of new disaster risk management in smart cities are discussed in this paper, and corresponding strategies are provided. This study not only enriches the risk studies of smart cities but also provides important theoretical and methodological references for emergency management of smart cities.

Humanities and Social Sciences CommunicationsVol. 13(1)
Anhui University of Science and Technology (CN), China University of Mining and Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Sustainable cities and communities
Openalex Percentile: Top 76%
Smart Cities and Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.