Reducing greenhouse gas emissions has become a critical global challenge, with growing attention in recent years. Transportation is a major contributor, ranking second after electricity and heating, making greenhouse gas (GHG) emission management vital for energy, automotive, and industry sectors. Electrical vehicles (EV) are seen to be an indispensable solution to mitigating greenhouse gas emissions. EV adoption through countries varies. Clustering countries according to some characteristics might reveal some common aspects of countries, additionally, the insights gained from these clusters could provide valuable guidance for policy adjustments aimed at promoting EV adoption. For this reason, this study aims to cluster countries using k-means algorithm using Gross Domestic Product (GDP) and number of fast charger units for EVs as parameter. According to the results, six clusters are formed where each cluster shows a specific pattern using the parameters. The clusters represent different characteristics of countries shaped by EV adoption of specific countries. As the clustering results reveal, China stands alone as a cluster itself showing its unique attributes whereas Norway stands in a cluster together with Iceland showing their unique path. Türkiye appears in a cluster of emerging markets, underlining its developing yet growing role in the global EV landscape.
Cebelli et al. (Thu,) studied this question.