Data-Driven Analysis of Transportation Route Efficiency and Carbon Emission Correlation in Retail Distribution Networks
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Abstract
Transportation networks coordinate intricate patterns of efficiency and sustainability within retail distribution systems. This study quantitatively examines the relationships between route optimization parameters and carbon emission trajectories through an extensive empirical analysis encompassing 2,847 distinct delivery routes. Statistical evaluations-using Pearson correlation (r = -0.742, p < 0.001) and Spearman rank analysis-reveal strong interdependencies between operational efficiency and environmental impact indicators. Multivariate regression models accounting for 73.8% of emission variance demonstrate that strategic route consolidation enhances operational efficiency by 23.7% and reduces emissions by 18.4% (quasi-experimental estimate: 19.3%; see Section 4.2). Among all variables, load factor optimization exhibits the highest correlation with emission reduction (r = -0.836). The derived performance metrics integrate both operational and environmental dimensions, highlighting that urban networks possess an optimization potential of 21.4%, significantly surpassing rural networks at 12.8%. Notably, operational optimization alone achieves 78.4% of the theoretical emission reduction potential without the necessity of additional technological interventions.
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