An IFS-IVIFS-DEMATEL Method to Identify Critical Success Factors of Cross-Department Coordination of Emergency Management

Cross-Department Coordination of Emergency Management (CDCEM) is considered a critical dimension in China to solve the problem of emergency management. The Decision Experiment and Decision-Making Trial and Evaluation Laboratory (DEMATEL) is a method used to build the structural correlation of criteria in uncertain environments to identify critical success factors (CSFs). There are coupling correlations and one-way correlations for interrelationship comparisons between selected factors of CDCEM. Therefore, there are two different assessment scales. However, most previous studies applied the DEMATEL method with a single assessment scale to identify CSFs. To fill this gap, an IFS-IVIFS-DEMATEL method is provided to comprehensively identify the CSFs of CDCEM in this study. The intuitionistic fuzzy set (IFS) is regarded as the assessment scales of coupling correlation, and the interval-valued intuitionistic fuzzy set (IFIVS) is regarded as the assessment scales of one-way correlation. The two different types of assessment scales were transformed into interval information in the improved approach. Then, using the conduction correlation among factors, a comprehensive correlation matrix was constructed. After that, the ranking of the central degree and cause degree of the factors according to the traditional DEMATEL method was obtained. Finally, a case study of Nanjing's CDCEM was illustrated to demonstrate that the proposed method is more suitable and reasonable. It is found that the factors of "cross-department organization", "cross-department information communication and transmission", "information sharing technology platform", "cross-department material supply capability", and "cross-department prediction and early warning" in Nanjing are CSFs in CDCEM, which should be emphasized to strengthen CDCEM. The findings of this study shed light on the cross-department coordination of emergency management mechanisms in uncertain situations, which would be beneficial for improving the efficiency of governmental management.