Factors influencing the utilization of electric vehicle charging stations: A socioeconomic perspective

초록

Currently, the penetration rate of electric vehicle (EV) charging stations is increasing; however, low utilization rates and the saturation of certain EV charging stations remain major issues. To efficiently install EV charging stations, this study analyzes the socioeconomic factors associated with their utilization based on EV charging records obtained from charging stations in Seoul, an urban center, primarily in 2022, and applies the same procedure to the 2024 charging records under the same analytical settings for year-to-year comparison. This study is distinct from previous research in that it analyzes EV charging stations by facility type and explicitly addresses multicollinearity using a genetic algorithm–based weighted scoring model, with principal component analysis (PCA) and Lasso regression used as benchmark methods. The analysis is conducted separately for gas stations, department stores, and hypermarkets, and the correlations with charging energy are improved by reorganizing the variable set through correlation and variance inflation factor analysis and optimizing weights using a genetic algorithm. The proposed model exhibits stronger correlations with the charging energies at EV charging stations than conventional models. Specifically, for gas stations, the proposed model achieves a correlation coefficient of 0.5865 compared with 0.4016 for the reference model; for department stores, the corresponding values are 0.7571 and 0.6858; and for hypermarkets, 0.6474 and 0.2979, respectively. Additionally, this study reveals that different types of facilities have different characteristics associated with charging energy at EV charging stations in metropolitan areas, providing guidance for optimizing the placement of charging stations across various facility types. Copyright © 2026. Published by Elsevier Ltd.

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