Prioritizing Subway Station Entrance Attributes to Optimize Passenger Satisfaction in Cold Climate Zones: Integrating Gradient Boosting Decision Trees with Asymmetric Impact-Performance Analysis

Subway station entrances serve as crucial links between urban environments and underground transit systems and are particularly vital in cities with cold climates. Specialized design strategies are essential to address user needs and promote safety and comfort, thereby encouraging sustainable travel in harsh winter conditions. This research utilizes data from Harbin and Shenyang, two winter cities in China, to explore the nonlinear influences of subway entrance attributes on passenger satisfaction through the combined use of gradient-boosting decision trees and asymmetric impact-performance analysis. The findings indicate that most key attributes of subway entrances impact passenger satisfaction asymmetrically, highlighting the significance of their hierarchical importance in generating satisfaction. These attributes are categorized into frustrators, dissatisfiers, hybrids, satisfiers, and delighters, based on their asymmetry levels. Considering the current performance of these attributes, the study identifies priority for improvement at Harbin and Shenyang’s subway entrances. This aids urban designers and city managers in making informed decisions for urban development and enhancing the overall commuter experience in winter cities.