A Comparative Study of SMAA-VIKOR and SMAA-TOPSIS in Urban Redevelopment Potential Evaluation in Guangzhou: Effectiveness and Spatial Insights

Abstract

Urban renewal decision-making involves balancing complex and often conflicting spatial, environmental, and socio-economic factors. This study compares two stochastic multi-criteria decision-making methods—SMAA-VIKOR and SMAA-TOPSIS—to evaluate community-level redevelopment potential in Guangzhou’s central urban area. By constructing a comprehensive evaluation framework that includes land and building characteristics, public service coverage, environmental quality, and socio-economic conditions, this study adopts the two algorithms to categorize 912 communities into four levels of renewal potentials and compare their performance by validated redevelopment projects’ sites. The result shows that SMAA-VIKOR yields more accurate and spatially coherent classifications, with 83% of projects located in high or medium potential zones, compared to 50% under SMAA-TOPSIS. It reveals that SMAA-VIKOR better captures trade-offs among indicators and provides a more balanced and policy-relevant basis for prioritizing renewal interventions. This research contributes a robust, scalable framework for data-driven urban renewal evaluation and offers practical insights for cities aiming to integrate spatial analytics into planning decisions under uncertainty.