An interpretable LightGBM-SHAP analysis of self-balance in Barcelona’s DBS stations

Abstract

Docked bike-sharing systems (DBS) play a pivotal role in promoting sustainable urban mobility by facilitating active travel and reducing motorized congestion. However, their long-term efficiency relies on each station’s ability to self-balance under temporally and spatially uneven demand. This study investigates the intrinsic self-balancing behavior of Barcelona’s Bicing network throughout 2024, encompassing 412 stations at a daily resolution. We introduce a station self-balancing index ( SSI )—a normalized indicator capturing day-to-day dock-availability variability—and employ a LightGBM–SHAP framework to quantify nonlinear associations among spatial, climatic, and temporal factors. Results show that spatial attributes, particularly residential and recreational points of interest (POIs) and building density, account for roughly two-thirds of the model-explained variance in SSI . SHAP interaction analyses further reveal that weekday work-oriented flows are associated with higher imbalance levels, whereas leisure-oriented urban morphologies help stabilize weekend operations. Overall, the findings provide interpretable, data-driven insights for enhancing DBS planning and operations, while offering a generalizable framework for assessing the self-regulatory capacity of urban micromobility systems.