Causation of Metro Operation Accidents in China: Calculation of Network Node Importance Based on DEMATEL and ISM

Author:

Wan Xin12ORCID,Zhang Yantong12ORCID,Wang Rubing12ORCID,Yuan Jingfeng3ORCID,Hu Mengliu1ORCID,Li Ruyu1ORCID,Wang Minye1ORCID,Huang Ziyao1ORCID,Tu Cheng4ORCID,Zhong Fujian1ORCID,Cui Wenjing1ORCID

Affiliation:

1. School of Business, Hohai University, Nanjing 211100, China

2. Institute of Engineering Management, Hohai University, Nanjing 211100, China

3. Department of Construction and Real Estate, Southeast University, Nanjing 210096, China

4. The Architectural Design & Research Institute of Zhejiang University Co., Ltd., Hangzhou 310027, China

Abstract

Continuous metro-operation accidents lead to serious economic loss and a negative social impact. The accident causation analysis is of great significance for accident prevention and metro operation safety promotion. Network node importance (NNI) evaluation has been widely used as a tool for ranking the nodes in complex networks; however, traditional indicators such as degree centrality (DC) are insufficient for examining accident networks. This study proposed an improved method by integrating decision making trail and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) into traditional NNI evaluation, where the key nodes are determined by both the nature of the accident network topology and the contribution of the nodes to accident development. Drawing on this method, 32 accident causal factors were identified and prioritized on the ground of 248 accident cases. It was found that 14 important factors related to staff (e.g., “driver noncompliance”), environment (e.g., “extrinsic nature disturbance”), passenger (e.g., “passenger sudden illness”), and machine (e.g., “track failures”) should be given priority in safety management due to their significant tendency of causing metro accidents. Theoretical and managerial implications were discussed to provide useful insights into the understanding of the causation of metro accidents and form a basis for metro managers to develop targeted safety countermeasures related to metro operation. The proposed hybrid method is proven effective in investigating accident networks involving sequential and casual relationships and revealing factors with high possibility to increase accidents.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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