Neutrosophic Fuzzy Selected Element Reduction Approach (NF-SERA): Assessment of E-Scooter Parking Area

Along with awareness of global warming, there have been many developments in recent years on carbon emissions in transportation. The use of micromobility vehicles has become widespread due to reasons such as energy saving, reducing carbon footprint and reducing traffic density in urban transportation. Although there are useful applications, this new concept has brought with it some problems. It is clear that new regulations are needed on issues such as accessibility, parking areas, security, charging stations, city planning etc. and the big cities need to adapt. Therefore, the carbon neutral districts have been started to be tested in small areas in many parts of the world and their effects are observed. This study performs Selected Element Reduction Approach (SERA), which is a Multi Criteria Decision Making (MCDM) criterion weighting method to determine the weight of the criteria to be used to assess the parking area of e-scooters in carbon neutral areas. SERA is a fuzzy environment MCDM method that aims to give weight to the criterion by the absence effect, which occurs by subtracting the criteria from the general evaluation. In this study, SERA is extended for the first time with single-valued neutrosophic fuzzy sets (SVNFS), which is a three-dimensional fuzzy environment. This study contributes to the literature by analyzing the application of NF-SERA with a numerical example. It also assesses the criteria for the e-scooter parking case for the carbon neutral areas that are currently discussed in the sustainable urban transportation literature.