Introducing R& Z-number cognitive map method for modeling the causal relationships of strategies (Case study: Iran health insurance organization)

We always face a range of ambiguity, uncertainty and risk in variables in qualitative, non-numerical and expert-centered issues. The root of this ambiguity can be in the variable itself or other variables related to it and the statements of experts. Fuzzy cognitive mapping is one of the common models for better understanding of problems that pays attention to the cause-and-effect relationship between variables. When dealing with problems where the numerical data associated with it are not available or the nature of the problem is qualitative, perceptual mapping is made by experts. One of the problems of using the common cognitive mapping model is not considering the uncertainty, risk and error in the opinions of experts. This problem affects the quality and validity of models created in complex problems. In this paper, in order to help understand the problem correctly and eliminate uncertainty, ambiguity and risk in experts' comments on variables and cause-and-effect relationships between them, the combined approach of Z-number and R-number in fuzzy cognitive mapping has been used. The proposed method in this article, by considering optimistic, pessimistic and neutral experts, has modeled the cause-and-effect relationships between strategies affecting the empowerment of individuals in the health system. The proposed approach of this research can be effective as a decision support method in issues that are qualitative and expert in nature.