Dynamic network data envelopment analysis model with fuzzy inputs and outputs: An application for Iranian Airlines

Abstract

Dynamic network data envelopment analysis (DNDEA) is a non-parametric model for evaluating the relative efficiency of decision-making units (DMUs) with network structure in several periods of time. The model uses accurate inputs/outputs data, whereas in many real-world applications, the data often fluctuate. Frontier-type models such as DNDEA models are sensitive to existence uncertainties in data. To deal with fluctuations in data which can be represented by fuzzy numbers, this paper extends the DNDEA model in a fuzzy framework. Since, the efficiency measures are expressed by membership functions rather than by certain values, hence, more information is provided for management. By using the proposed fuzzy DNDEA model, the precise efficiency scores in DNDEA model are extended to the fuzzy numbers for reflecting uncertainty in real evaluation problems. The final efficiency scores generated by the proposed model are intervals which can describe the real situation in better detail. In addition, the proposed model is a useful tool for detecting sensitive decision-making units. To illustrate the capability of the proposed fuzzy DNDEA model, a case study of airlines in Iran is used to explain how the efficiencies of system and process with fuzzy data are calculated.