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<p>Amid accelerating urbanization and stringent sustainability targets, cities face acute challenges in prioritizing sustainable urban development projects (SUDPs) under tight budgets and policy deadlines. Traditional binary evaluation frameworks often misclassify borderline projects and are distorted by redundant criteria. We introduce a three-phase evidence-based decision framework that integrates (1) grey clustering model (GCM) to eliminate indicator redundancy while preserving conceptual coverage, (2) a difference-driven technique for order preference by similarity to ideal solution (TOPSIS) model for objective weighting and ranking, and (3) a three-way decision (TWD) mechanism with risk-averse thresholds calibrated via the analytic hierarchy process (AHP). Applied to ten competing SUDPs in Xi’an, China, the framework delivered decisive actions: it approved four projects outright, deferred one for targeted refinement, and rejected the remainder. Comparative analysis revealed that only the TWD model produced unequivocal accept/reject/defer recommendations without arbitrary cutoffs, whereas TOPSIS, fuzzy comprehensive evaluation (FCE) and grey fixed-weight clustering (GFWC) either required subjective threshold setting or failed to handle borderline cases. Sensitivity analysis across eleven risk levels confirmed stable outcomes and a smoothly shrinking defer zone, proving robust adaptability. The modular design equips urban planners worldwide with a transparent, replicable tool for strategic, risk-informed SUDP selection.</p>

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A three-way decision framework integrating grey clustering and TOPSIS for sustainable urban project prioritization

  • 期刊论文

  • 发表日期：

    2026年1月16日

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  • Fan Zhang,
  • Shengbin Li,
  • Xiong Zhang,
  • Qian Zhao

摘要

Amid accelerating urbanization and stringent sustainability targets, cities face acute challenges in prioritizing sustainable urban development projects (SUDPs) under tight budgets and policy deadlines. Traditional binary evaluation frameworks often misclassify borderline projects and are distorted by redundant criteria. We introduce a three-phase evidence-based decision framework that integrates (1) grey clustering model (GCM) to eliminate indicator redundancy while preserving conceptual coverage, (2) a difference-driven technique for order preference by similarity to ideal solution (TOPSIS) model for objective weighting and ranking, and (3) a three-way decision (TWD) mechanism with risk-averse thresholds calibrated via the analytic hierarchy process (AHP). Applied to ten competing SUDPs in Xi’an, China, the framework delivered decisive actions: it approved four projects outright, deferred one for targeted refinement, and rejected the remainder. Comparative analysis revealed that only the TWD model produced unequivocal accept/reject/defer recommendations without arbitrary cutoffs, whereas TOPSIS, fuzzy comprehensive evaluation (FCE) and grey fixed-weight clustering (GFWC) either required subjective threshold setting or failed to handle borderline cases. Sensitivity analysis across eleven risk levels confirmed stable outcomes and a smoothly shrinking defer zone, proving robust adaptability. The modular design equips urban planners worldwide with a transparent, replicable tool for strategic, risk-informed SUDP selection.