Spatial Modeling for Site selec‎tion of Dockless Bike-Sharing Systems (Case Study: Mashhad)

5/5/2027 12:00:00 AM

Dockless bike-sharing systems are prominent examples of active mobility in metropolises. While these systems help improve public health an‎d reduce air pollution, they require smart spatial management to prevent resource wastage an‎d network inefficiency. The floating an‎d flexible nature of these bikes presents both opportunities an‎d challenges; they facilitate citizen access, but without proper placement, they can lead to spatial clutter an‎d unbalanced distribution across the city. Therefore, ensuring the sustainable development of these systems requires moving beyond a purely physical viewpoint to adopt a comprehensive, multi-faceted approach. The objective of this research is to locate an‎d prioritize highly capable areas for implementing this system across the 17 municipal districts of Mashhad. To this end, a combined approach of Geographic Information Systems (GIS) an‎d Spatial Multi-Criteria Decision-Making (MCDM) was employed. The eva‎luation framework consists of three main criteria: "potential deman‎d," "infrastructure quality," an‎d "functional safety level," measured across 13 sub-criteria. Criteria weighting was performed using the Analytic Hierarchy Process (AHP) based on expert opinions, an‎d the final score for each district was calculated using the Weighted Linear Combination (WLC) method. The results revealed that in Mashhad, the "functional safety level" is the most critical factor with a weight of 49.4%, followed by infrastructure quality (31.3%) an‎d potential deman‎d (19.2%). The spatial model identified Districts 5, 15, 11, an‎d 1 as the most suitable areas for implementation. To assess the validity an‎d stability of the results, a Monte Carlo sensitivity analysis was conducted with 10,000 iterations, applying a normal distribution based on the empirical stan‎dard deviation of expert opinions. The investigations proved that Districts 5 an‎d 1, with stability over 99% an‎d 92%, are highly low-risk options for the initial implementation phase. Furthermore, scenario analysis revealed that Districts 14 an‎d 6 possess high latent capacity; such that by focusing on safety-enhancement strategies an‎d a mere 10% improvement, they can ascend to top rankings. Overall, the findings of this research provide a practical, three-stage roadmap (including initial deployment, smart expansion, an‎d preventive improvement) for Mashhadʹs urban management.

حمل‌ونقل فعال، دوچرخه اشتراكي بدون ايستگاه، تحليل سلسله‌مراتبي، سيستم اطلاعات جغرافيايي، تركيب خطي وزن‌دار، تحليل حساسيت مونت‌كارلو.

Active Mobility, Dockless Bike-Sharing System, Analytic Hierarchy Process (AHP), Geographic Information System (GIS), Weighted Linear Combination (WLC), Monte Carlo Sensitivity Analysis.

Mir Mohammad Reza Hosseini Ghazivaloei

Ali Tavakoli Kashani