Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Fuzzy Multiple Attribute Decision Making: Methods and Applications
Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques
Multi-objective Group Decision Making: Methods, Software and Applications With Fuzzy Set Techniques
Developing a group decision support system based on fuzzy information axiom
Knowledge-Based Systems
An extended TOPSIS for determining weights of decision makers with interval numbers
Knowledge-Based Systems
Credit risk assessment and decision making by a fusion approach
Knowledge-Based Systems
Generalized hesitant fuzzy sets and their application in decision support system
Knowledge-Based Systems
Analysing network uncertainty for industrial product-service delivery: A hybrid fuzzy approach
Expert Systems with Applications: An International Journal
An approach to generalization of fuzzy TOPSIS method
Information Sciences: an International Journal
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With the ever increasing public awareness of complicated road safety phenomenon, much more detailed aspects of crash and injury causation rather than only crash data are extensively investigated in the current road safety research. Safety performance indicators (SPIs), which are causally related to the number of crashes or to the injury consequences of a crash, are rapidly developed and increasingly used. To measure the multi-dimensional concept of road safety which cannot be captured by a single indicator, the exploration of a composite road safety performance index is vital for rational decision-making about road safety. In doing so, a proper decision support system is required. In this study, we propose an improved hierarchical fuzzy TOPSIS model to combine the multilayer SPIs into one overall index by incorporating experts' knowledge. Using the number of road fatalities per million inhabitants as a relevant reference, the proposed model provides with a promising intelligent decision support system to evaluate the road safety performance for a case study of a given set of European countries. It effectively handles experts' linguistic expressions and takes the layered hierarchy of the indicators into account. The comparison results with those from the original hierarchical fuzzy TOPSIS model further verify the robustness of the proposed model, and imply the feasibility of applying this model to a great number of performance evaluation and decision making activities in other wide ranging fields as well.