Gis-based site selection for e-waste collection bins with hesitant fuzzy MCDM approach

Due to the development of technology and its spread to different areas, the use of technological devices has been increasing rapidly in recent years. Technological devices that have completed their useful life cause an increase in the type of waste called electronic waste. E-waste threatens human health by mixing with air, soil and water if its recycling or disposal cannot be carried out in a controlled manner by authorized institutions due to the harmful substances they contain. On the other hand, e-waste contributes to the economy by recycling due to the precious metals they contain. According to the Regulation on the Control of Waste Electrical and Electronic Equipment published in the Official Gazette, these wastes are examined in 6 groups. In this study, it is aimed to determine the most suitable locations in Atakum district of Samsun province for e-waste bins, which are responsible for the Turkish Informatics Industry Association, which is the organization authorized in 2015 by the Ministry of Environment, Urbanization and Climate Change to collect electrical and electronic waste in the 3rd and 4th categories. In this regard, first of all, with the support of five leading experts and in line with studies in the literature, nine criteria that are important in positioning e-waste bins were determined. Then, these criteria were weighted with the Hesitant Fuzzy SWARA method. Afterwards, data sets were created with the help of Geographic Information Systems (GIS) and maps were obtained for each criterion. Euclidean Distance and Kernel Density Estimation were used when creating the maps. Subsequently, the maps were normalized between 0 and 1, and a suitability map was created using the weighted sum method, taking into account the criterion weights. Alternative points for e-waste collection bins were obtained with this map. The obtained alternative points were ranked with the TOPSIS method, and in the last part, sensitivity analysis was conducted with two different scenarios in order to see how the change in criteria weights affected the ranking of the alternatives.