The multimodal dynamics of “ride-pooling” and metro: Spatial-temporal patterns from East Asia

“Ride-pooling” services provided by transportation network companies have gained substantial popularity and demonstrate significant potential for integration with mass rapid transit to form competitive multimodal transportation options. However, data-driven studies on these services, particularly those using spatial-temporal analysis, remain complex and underexplored. This study examines the intricate relationship between ride-pooling and metro services through a large-scale dataset from Suzhou, China, focusing on identifying cooperative and competitive dynamics between the two modes, classifying multimodal trips that include both ride-pooling and metro services, and uncovering spatial-temporal patterns within these interactions. The analytical framework incorporates joint methods such as time-sequence analysis, non-negative matrix factorization, and metro passenger origin-destination matrix inference to achieve the study's objectives. Findings reveal that 4.26 % of all ride-hailing trips were pooled rides, while multimodal trips involving transfers between ride-pooling and mass rapid transit accounted for 13.5 % of total trips, offering economic benefits for users. These multimodal trips primarily cater to commuting demands and exhibit distinct, imbalanced peak-hour usage patterns. Spatial analysis indicates that the majority of these trips occur in suburban and outskirt areas, where mass rapid transit coverage is limited and correlates strongly with “industrial” land use. The distribution of corresponding metro trips shows similar spatial patterns. This research provides new insights into the integration potential of ride-pooling and metro services, highlighting critical multimodal spatial-temporal patterns. • A universal algorithm to identify city-level ride-pooling (RP) trips is proposed, mainly serving regulatory bodies. • RP trips account for 4.26 % of the total ride-hailing, while transfer-type RP trips account for 13.5 %, showing economic benefits for users. • Transfer-type RP services are essential for connectivity in suburban and outskirt regions with limited metro access. • Multimodal trips between the RP and metro mainly serve commuting demands, especially for morning peak hours. • Industrial zones exhibit the highest correlation with RP-metro multimodal trips.