Construction of interpretive structure modeling for the influencing factors of emergency industry development

Issue title: Cross-domain Applications of Fuzzy Logic and Machine Learning

Guest editors: Ekaterina Isaeva and Álvaro Rocha

Article type: Research Article

Authors: Liu, Yuliang^a | Kang, Canhua^a | Yin, Zongyi^{b; *}

Affiliations: [a] School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, Hubei, China | [b] School of Law, Humanities and Sociology, Wuhan University of Technology, Wuhan, Hubei, China

Correspondence: [*] Corresponding author. Zongyi Yin, School of Law, Humanities and Sociology, Wuhan University of Technology, Wuhan, 430070, Hubei, China. E-mail: yinzongyi1984@163.com.

Abstract: Promotion of the emergency industry plays a major role in pacing up adjustment of industrial structure and enhancing economic vitality. Eleven influencing factors of the emergency industry were explored from economic, social and environmental aspects and the ISM (Interpretive Structure Modeling) model of the emergency industry was constructed by using basic methods of ISM. Results show that investment in emergency industry, input-output efficiency of emergency industry and application of technological innovation in emergency industry are the most direct factors affecting the development of emergency industry at present, while public safety consciousness is the most fundamental factor affecting emergency industry.

Keywords: Emergency industrial, influencing factors, index system, interaction mechanism, ISM

DOI: 10.3233/JIFS-179771

Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 6, pp. 6927-6935, 2020