Application of Hierarchical Clustering Algorithm to Classify Docked Bike-Sharing System Stations

This study applied the hierarchical clustering algorithm to categorize bike-sharing system stations operating in İzmir, Türkiye, based on their temporal usage patterns. By distinguishing between transportation- and leisure-oriented trips, the research provides insights into the operational dynamics of the system. The findings highlighted spatial and temporal distinctions, with Konak İskele Station consistently emerging as a separate cluster for transportation-oriented trips, indicating its crucial role due to its central location and proximity to public transportation hubs. In the case of leisure-oriented trips, the analysis revealed three clusters on weekdays, with Konak İskele Station maintaining its prominence, particularly in the afternoon and late evening hours. However, weekend trips were characterized by the identification of two main clusters. These results emphasize the importance of tailored management strategies for bike-sharing systems, suggesting that transportation-oriented trips may benefit from more strategic station placements and enhanced connectivity to public transit.