A new intuitionistic fuzzy scheme of data envelopment analysis for evaluating rural comprehensive health service centers

In this study, the classical CCR-IO DEA model (an input-oriented form of the DEA model of Charnes, Cooper, and Rhodes (1978)) is extended to an intuitionistic fuzzy environment. For this aim, the trapezoidal intuitionistic fuzzy numbers are used to show the values of inputs and outputs. An intuitionistic fuzzy number is characterized by membership, non-membership, and hesitancy degrees. Therefore, such type of fuzzy numbers is more complete and contains more information to reflect a fuzzy type of uncertainty comparing to the conventional fuzzy values. In order to solve the proposed intuitionistic fuzzy CCR-IO model, for the first time a possibility-based approach is developed for the intuitionistic fuzzy DEA models. In this approach for the first time the $$ measure of fuzzy events is extended to intuitionistic fuzzy DEA models, therefore, some new definitions and propositions are presented and clarified. This measure is more flexible and effective comparing to the other measures such as credibility, necessity, and possibility measures. A case study from the health care sector of Iran is considered to evaluate the proposed solution approach numerically. The case study is solved under different scenarios, a full sensitivity analysis is performed, and finally some useful managerial insights are presented. In addition, the results of the proposed intuitionistic CCR-IO model are compared to the classical models of the literature.