System dynamics evidence of sub-additive carbon reduction from combined mitigation strategies in multi-echelon logistics networks

The transition of multi-echelon logistics networks toward carbon neutrality is constrained by the inability of traditional static models to capture complex emission dynamics and time-delayed effects. To bridge this critical gap, this study develops a comprehensive system dynamics framework that captures non-linear feedback mechanisms, nonlinear interactions and temporal delays across transportation, inventory, and ware-housing operations. By simulating multiple mitigation strategies on a stylized regional distribution network, the analysis reveals strongly asymmetric temporal patterns: annual emissions in the base scenario rise from 2,736 to 3,453 t CO 2 e over five years, an increase of 26.2%. Transportation mode optimization delivers a 21.3% reduction with a 9.8% saving in five-year total cost, network reconfiguration a 22.4% reduction with a 6.5% saving, and technology upgrading a 25.9% reduction at an 8.4% cost increase. Combining all three yields a 47.5% reduction while lowering cumulative expenditure by 9.8%, so the deepest reduction is obtained together with a net cost saving rather than in exchange for one. The combined effect is markedly sub-additive, since the three single strategies sum to 69.6% points against a simulated 47.5. The emission response to modal shift is near-linear in the shifted volume over the range a programme can plausibly reach, and a shift of 57.6% of road line-haul tonne-kilometres is required merely to hold year-five emissions at the base-year level. Theoretically, these findings challenge prevailing static optimization paradigms by reframing logistics networks as complex adaptive systems. Practically, the study provides a transparent and reproducible simulation framework with which logistics managers can examine the sequencing and interaction of decarbonization measures before committing capital.