Using AHP-Entropy Method to Explore the Influencing Factors of Spatial Demand of EVs public charging stations: A Case Study of Jinan, China

Abstract

In global sustainability efforts, electric vehicles (EVs) represent a burgeoning trend in the green transformation of the automotive sector. Widespread EVs adoption is closely associated with the availability of public charging stations (PCS). Understanding the factors that affect spatial demand for PCS is crucial for accurately measuring user needs and optimizing placement strategies. This study employs a geographical information system (GIS) to develop a spatial visualization evaluation index system including five dimensions: population distribution, traffic organization, infrastructure, land use, and regional economy. This research utilizes an AHP-Entropy method to rigorously analyze the weights of various spatial factors affecting the spatial demand of PCS for EVs. This findings indicate that: 1) Infrastructure (0.403) has the greatest impact on the spatial demand for PCS, followed by traffic organization (0.356), regional economy (0.129), land use (0.066), and population distribution (0.046). 2) Of the 14 indicators, the betweenness of road network (0.292) is the most important influencing factor. In addition, the scale of commercial centers (0.144), the scale of park views (0.104), nighttime light distribution (0.094), and the scale of transportation stations (0.090) are also key factors. By integrating both subjective and objective factors in spatial geography, this study offers a comprehensive evaluation of factors influencing spatial demand for PCS. The article concludes by proposing PCS spatial layout strategies from five dimensions, thereby promoting the further development of the EVs industry from a low-carbon perspective.