designing a new case of two-stage dea model about the indirect relation of information technology investment on firm performance in intuitionistic fuzzy environment

Data envelopment analysis (dea) is a theoretical framework for performance analysis and efficiency measurement. traditional dea models, which measure the efficiency of simple decision-making with multiple inputs and outputs, have several weaknesses, one of which is the inability to consider intermediate variables. therefore, network data envelopment analysis (ndea) has been developed to address this issue, which is especially important for the analysis of two-stage processes. also, since real-world data often are non-deterministic and imprecise, fuzzy sets theory and intuitionistic fuzzy sets theory, which are well-equipped to handle such information, can be used to improve the performance of two-stage dea models. in this study, firstly ndea models are discussed and then multiplicative method of ndea is stated to obtain the individual efficiencies and the overall efficiency of the two stages. also, it is explained how these models can be modified with intuitionistic fuzzy coefficients, and finally is described how arithmetic operators for intuitionistic fuzzy numbers can be used for a conversion into crisp two-stage structures. this paper presents a new two-stage dea model to study the indirect impact of information technology investment on firm performance operating based on fuzzy intuitionistic numbers. using this model, the efficiency of the first and second stages of a two-stage decision-making and ultimately its overall efficiency can be estimated with due to intermediate variables. the proposed method is used to solve a numerical example containing 12 dmus with intuitionistic fuzzy triangular number coefficients.