Multi-criteria Prioritization of Shared Mobility Hub Locations: An Integrated BWM-TOPSIS Approach

Abstract

Strategic investment in shared mobility infrastructure necessitates balancing multiple conflicting criteria. This study develops and applies an integrated Best-Worst Method (BWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework to prioritize urban zones for shared mobility hub investment in Budapest, Hungary. Vector normalization was adopted in the TOPSIS stage for its scale-invariance properties, ensuring robust cross-criteria comparability. The methodology incorporates 17 sub-criteria across five main dimensions: Transport Connectivity, Demand Density, Infrastructure Readiness, Environmental Impact, and Social Equity. Expert judgments were synthesized using BWM and applied to evaluate four distinct urban typologies: the Historic Central Business District (Zone A), Mixed-Use Residential Corridor (Zone B), Major Transport Hub & University Area (Zone C), and Residential Suburb (Zone  D).
Results identify Zone B (Újlipótváros - Angyalföld) as the top priority, offering the best balance between high demand and implementation feasibility. Zone A (Belváros - Lipótváros), the historic CBD, ranks second, as its superior connectivity is offset by severe spatial constraints. Zone C (Kelenföld - Albertfalva), a major transport hub, places third, while Zone D (Péterhegy - Kőbánya), a residential suburb, ranks fourth due to lower current connectivity despite strong environmental and social equity scores.
The analysis reveals a core planning trade-off: zones with the highest immediate demand face the greatest physical implementation challenges. The proposed framework provides municipal planners with a transparent, quantitative tool for optimizing phased infrastructure investment, with future work recommended to incorporate real-time and time-dependent mobility data for dynamic scenario analysis.