Promotion strategy of low-carbon multimodal transportation considering government regulation and cargo owners’ willingness

Hu, Xinghua; Cheng, Ruizi; Zhao, Jiahao; Wang, Ran; Zhang, Tingting; Lei, Hao; Liu, Ba

doi:10.1007/s10668-024-04829-6

Cited by 1 publication

(1 citation statement)

References 53 publications

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“…Furthermore, Hu et al [50] investigate the impact of economic and regulatory factors, such as regulatory costs and carbon taxes, on environmental sustainability and economic efficiency. They propose a balanced approach that aligns incentives for cost and emission reductions.…”

Section: Logistic Regression Modelmentioning

confidence: 99%

Pursuing Optimization Using Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

Derpich,

Duran,

Carrasco

et al. 2024

JMSE

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The core problem of a multimodal transportation system is integrating various transportation modes into a cohesive, efficient, and user-friendly network. This study introduces a novel centralized load concentration approach for regions facing geographic challenges. The principal aim is improving multimodal transportation systems by mitigating CO2 emissions and improving operational efficiency. This will significantly reduce high logistics costs and the environmental impact caused by greenhouse gas emissions, particularly in land transportation, aligning with the global sustainable development goals and offering a promising path towards a more sustainable future. The proposed method implicates direct cargo transportation from its origin to the export ports without passing through intermediate centers. The mathematical model determines the most efficient means of transportation for each route, considering variables such as distance, volume, and type of cargo. Research results indicate that multiple hubs may not be necessary in scenarios with high freight concentration, which could streamline transportation and logistics operations. The modal preferences vary depending on regional dynamics and cargo characteristics, with rail and sea transport emerging as preferable options in specific circumstances, outperforming road transport. The proposed model shows reductions in logistics costs and CO2 emissions compared to road-focused scenarios. This study provides an adaptable framework for optimizing multimodal transportation systems in regions with similar geographic and logistical attributes. It offers a versatile solution to various contexts and needs. Lastly, the strategic integration of multiple modes of transportation is fundamental to improving efficiency and sustainability.

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Section: Logistic Regression Modelmentioning

confidence: 99%