Description
With rising interest in electric mobility, the need for Electric Vehicle Charging Stations (EVCS) increases. Since few attempts have been made to address this problem, a visualized Geographic Information System (GIS) approach using geospatial data and a weighted multicriteria analysis considering the proximity to users and the existing energy grid have not been developed yet. Since the visualization of decision problems has been found to be beneficial for decision processes, our goal is to design a Spatial Decision Support System using an AHP approach to support decision-makers to identify suitable locations for EVCS using a GIS to map and visualize the results. We use design science research to design our system as a prototype and find that implementing an AHP approach within a GIS application offers potential to increase added value for decision-making processes.
Recommended Citation
Priefer, Jennifer and Steiger, Lennart, "Designing a GIS-AHP-Based Spatial Decision Support System for Discovering and Visualizing Suitable Locations for Electric Vehicle Charging Stations" (2022). Wirtschaftsinformatik 2022 Proceedings. 31.
https://aisel.aisnet.org/wi2022/prototype_track/prototype_track/31
Designing a GIS-AHP-Based Spatial Decision Support System for Discovering and Visualizing Suitable Locations for Electric Vehicle Charging Stations
With rising interest in electric mobility, the need for Electric Vehicle Charging Stations (EVCS) increases. Since few attempts have been made to address this problem, a visualized Geographic Information System (GIS) approach using geospatial data and a weighted multicriteria analysis considering the proximity to users and the existing energy grid have not been developed yet. Since the visualization of decision problems has been found to be beneficial for decision processes, our goal is to design a Spatial Decision Support System using an AHP approach to support decision-makers to identify suitable locations for EVCS using a GIS to map and visualize the results. We use design science research to design our system as a prototype and find that implementing an AHP approach within a GIS application offers potential to increase added value for decision-making processes.