Investigating the Relationship between Bus Network Topology and Temporal Ridership Patterns: A Case Study in Singapore

To advance the understanding of passenger temporal ridership profiles in urban bus systems, this study examined the relationship between network topological characteristics and temporal ridership patterns. Using Singapore’s bus system as a case study, stop-level hourly passenger profiles were constructed, and a clustering approach was applied to identify five typical temporal patterns: mixed-use central business district (CBD), western job hubs, peripheral residential regions, near-central residential regions, and school-oriented zones. Adopting the complex network theory, the bus network was represented in both L-space and P-space, allowing computation of key topological descriptors and examination of degree distributions and small-world features. A multinomial logit (MNL) model was employed to investigate the relationships between temporal ridership clusters and network topology. The results confirm significant associations and indicate that residential origins exhibit stronger outward connectivity and bridging roles, whereas job and school destinations demonstrate concentrated inflows and high local transitivity within dense route cliques. Additionally, incorporating network topology significantly improves model performance, highlighting that network context provides additional explanatory power for temporal ridership patterns beyond the urban environment alone. By linking network topology with temporal ridership dynamics, this study provides a network-based perspective that can inform more-efficient and -adaptive public bus network planning.