A Spatial Decision-Making Framework for Electric Vehicle Charging Station Planning in Hot-Climate Cities: A Case Study of Kuwait

With the growing adoption of electric vehicles, the proper siting of electric vehicle charging stations (EVCSs) has become a critical issue in urban transportation planning. This study addresses the EVCS siting problem in Kuwait through a spatial decision-making approach. A total of 25 spatial criteria covering transportation, land use, environmental conditions, and energy infrastructure were evaluated. Criterion weights were calculated from expert judgments using the Fuzzy SIWEC and SWARA methods. The results showed a high level of consistency between the two weighting methods, with a Spearman rank correlation coefficient of ρ = 0.9090 and a Pearson correlation coefficient of r = 0.8376. The final weights indicated that tourism, culture, and entertainment areas (C2.3, 0.05046), parking areas (C1.3, 0.04910), road accessibility (C1.4, 0.04813), and retail and dining areas (C2.6 to C2.7, 0.04708 to 0.04757) were the most influential factors in EVCS planning. All criteria were spatially represented in a geographic information systems environment, normalized to the [0–1] range according to their benefit and cost directions, and integrated through weighted overlay analysis to produce a continuous EVCS suitability map. Based on this suitability surface, 133 candidate EVCS alternatives were assigned to areas with relatively high suitability values and active urban land-use characteristics. The extracted raster suitability values of these candidate alternatives ranged approximately between 0.640 and 0.860, indicating that the assigned points were concentrated in spatially favorable areas rather than being randomly distributed. The ranking results obtained from TOPSIS and VIKOR showed that the top six alternatives were identical in both methods, and alternative A123 ranked first with a VIKOR value of 0.007548 and a TOPSIS value of 0.884213. Sensitivity analysis showed that changes in criterion weights affected suitability values and transition zones, while the overall spatial pattern of highly suitable areas remained stable. The findings suggest that the proposed GIS-MCDM framework provides a practical preliminary decision-support basis for spatial screening and investment prioritization in EVCS planning, particularly in hot-climate cities.