Identification and Prioritization of Key Factors Influencing Risk Management in Process Industries Using the Fuzzy DANP Method

Elham  Keighobadi; Hossein  Ebrahimi; Shahram  Vosoughi; Farhad  Asgharyan; Saber Moradi  Hanifi

doi:10.18502/jhsw.v16i1.21893

Elham Keighobadi Occupational Health Research Center, Department of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
Hossein Ebrahimi Department of Occupational Health and Safety Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
Shahram Vosoughi Department of Occupational Health and Safety Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
Farhad Asgharyan The Petroleum University of Technology, Abadan, Iran.
Saber Moradi Hanifi Department of Occupational Health and Safety Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran

DOI: https://doi.org/10.18502/jhsw.v16i1.21893

Keywords: Risk management, Process industries, Fuzzy DEMATEL, Fuzzy network analysis, Safety

Abstract

Introduction: Process industries are considered to be vital pillars of economic development, but thecomplexity of their performance and processes poses serious challenges to effective risk management.This study presents an integrated model based on Fuzzy DEMATEL and Fuzzy ANP methods to identify andprioritize key factors affecting risk management in these industries.

Material and Methods: First, in a systematic literature review, 54 eligible articles were selected fromreliable sources between 1995 and 2024, and 23 initial factors affecting risk management were extracted.Then, in three rounds of Delphi technique with the participation of 13 experts with an average workexperience of 12.6 years, 20 final factors were confirmed. Subsequently, the Fuzzy DEMATEL method wasused to analyze the cause-and-effect relationships between the factors, and the Fuzzy ANP method wasused to determine their weight and priority.

Results: The results indicated that 6 factors play a causal role, while 14 factors play an effect role.“Training” and “management commitment” were identified as the most effective causal factors, playing apivotal role in strengthening other risk management measures. In contrast, “maintenance and repair” and“contractor and stakeholder participation” were the most influenced by other factors. Additionally, “safetyculture and climate” obtained the highest weight in the fuzzy network analysis.

Conclusion: By providing a comprehensive picture of the influencing factors and their interactions, theproposed framework provides a practical and strategic tool for managers to improve process safety andmanage risks more effectively by focusing on priority factors