A multi-source data-driven evaluation framework for sustainable urban marathon course design

Urban marathon events have become an important component of modern cities. This study developed a multi-source, data-driven framework for evaluating urban marathon course design. Grounded Theory was used to identify key factors through semi-structured interviews, after which the resulting framework was refined and weighted using the Delphi method and the Analytic Hierarchy Process (AHP). The final framework comprised two primary indicators, four secondary indicators, and fourteen tertiary indicators and was applied to the Beijing, Shanghai, and Xiamen Marathon courses. The results showed that all three courses met the evaluated course specification requirements, but exhibited distinct characteristics across the evaluated dimensions. The Beijing Marathon course showed the highest landmark architecture density and a more stable elevation profile. The Shanghai Marathon course demonstrated stronger public transport accessibility, but also a higher number of sharp turns. The Xiamen Marathon course showed clear advantages in natural landscape coverage and greening rate, reaching 88.40% and 65.60%, respectively, while exhibiting comparatively lower pedestrian flow intensity. Overall, the proposed framework provides a practical approach for the comparative evaluation of urban marathon courses and may support more evidence-based course planning.