A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation

Abstract

Safety is a critical element in the air transport industry. Although fatal air accidents are rare compared to other transport industries, the rapid growth in air travel demands has resulted in a growing aviation risk exposure and new challenges in the aviation sector. Although the issue of airline safety is of serious public concern, notably few studies have investigated the safety efficiency of airlines. This paper aims to propose a novel hybrid method using fuzzy data envelopment analysis (DEA) and fuzzy multi-attribute decision making (F-MADM) for ranking the airlines' safety. In this study, fuzzy DEA is utilized to calculate criteria weights, in contrast to the conventional approach of using DEA for measuring the efficiency of alternatives. A ranking of each airline (DMU) on the basis of obtained weights is then assessed using MADM methods. Six MADM methods including Fuzzy SAW, Fuzzy TOPSIS, Fuzzy VIKOR, ARAS-F, COPRAS-F and Fuzzy MULTIMOORA are implemented to rank the alternatives, and finally, the results are compounded with the utility interval technique. This new hybrid method can efficiently overcome the pitfalls of traditional hybrid DEA-MADM models. The method proposed in this study is used to evaluate the safety levels of seven Iranian airlines and to select the safest one.