Selecting an airport ground access mode using novel fuzzy LBWA-WASPAS-H decision making model

Airports are critical in ensuring a fast way of transporting people and goods. Choosing a reliable, fast and comfortable access mode to the airport is vital to ensure a seamless aviation system. The aim of this study is to select the best transport mode for Istanbul’s newly constructed Istanbul Airport. One of the largest airports in the world with 150,000 passenger capacity per year, Istanbul Airport is located in the northern part of Istanbul, outside the city. However, the access to the new airport resulted in many controversies about the selection of the best mode. Underground metro, bus rapid transit (BRT), light rail transit (LRT) and premium bus services are put forward as alternative ground access modes. These alternatives are evaluated based on 4 main decision criteria including financial aspects, operating features, project characteristics and environmental sustainability, which are broken down into 14 sub-criteria. In this paper, the importance weights of the criteria are determined by novel fuzzy Level Based Weight Assessment (LBWA) which is capable of modelling human thinking. Afterwards, the traditional Weighted Aggregated Sum Product Assessment (WASPAS) method is enhanced by the integration of the fuzzy Weighted Heronian Mean (WHM) and fuzzy Weighted Geometric Heronian Mean (WGHM) functions. A hybrid fuzzy multi-criteria decision making method based on LBWA-WASPAS-H model is used to solve this ground access mode selection problem. The results show that an underground metro is the most optimal mode, followed by LRT, BRT, and premium bus services.