Urban agglomerations in developing regions face cascading inefficiencies in cold chain logistics, driven by structural dependencies on cross-regional distribution that generate excessive costs, carbon emissions, and quality deterioration. This study develops and empirically validates a systematic transformation framework that utilizes hierarchical optimization to reconfigure these inefficient networks into integrated, sustainable local systems. Our approach coordinates strategic facility location with operational vehicle routing, enabling emergent, system-level improvements that transcend conventional optimization. Empirical validation using 35 supermarket stores in the Hohhot-Baotou-Ordos-Ulanqab (HBOU) urban agglomeration demonstrates substantial, concurrent outcomes under practical conditions: a 44.1% reduction in both cost and carbon emissions, and a 21.9% enhancement in product freshness. Statistical analysis confirms high significance (p < 0.001), with a resulting Transformation Effectiveness Coefficient of 1.34, signifying a paradigm-level improvement. The framework reveals that apparent trade-offs between economic, environmental, and service objectives can be systematically resolved through strategic network reconfiguration. These findings advance urban logistics transformation theory by providing a reproducible, data-driven framework for designing sustainable distribution systems, offering significant policy and practical implications for comparable urban contexts globally.
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KeWei Wang (2025) studied this question.
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