Literature DB >> 32124302

Reducing carbon emissions from collaborative distribution: a case study of urban express in China.

Kexin Bi1, Mengke Yang2, Xiaoguang Zhou1, Latif Zahid3, Yufei Zhu1, Zhongyuan Sun4.   

Abstract

The booming development of e-commerce has brought about rapid growth in the express delivery industry in China. However, urban express distribution is increasingly difficult and seriously affecting the traffic, safety, and environmental conditions of cities due to small, scattered end points, unreasonable allocation of resources, and seriously repeated resource waste. Therefore, there is an urgent need to solve the problems associated with the unreasonable resource allocation of express distribution. In the context of green logistics, a new mode of collaborative distribution based on intelligent end service station (IESS) is proposed. Following the measurement models of carbon emissions, before and after collaborative distributions are provided to prove the environmental benefits of the new mode. The influencing factors considered in the models are the average daily distribution volume, number of distribution sections, vehicle ownership of various types, and their capacity, use, fuel, and power consumption. To verify the models' validity, we conduct an empirical study of five express enterprises in China and make a comparative analysis on the results, which show that the implementation of collaborative distribution can extremely reduce carbon emissions and improve the overall load rate of vehicles. Specially, the use of new energy vehicles can contribute significantly to energy conservation and emissions reduction.

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Keywords:  Carbon emissions; Collaborative distribution; Environmental benefits; Express delivery industry; Green logistics; Vehicle arrangement

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Year:  2020        PMID: 32124302     DOI: 10.1007/s11356-020-08143-2

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  1 in total

1.  A Decision Method for Benefit Distribution Mechanism of Shared End Distribution on Shapley Value.

Authors:  Hao Zhang; Yuan Hou; Feng-Feng He
Journal:  Comput Intell Neurosci       Date:  2022-02-14
  1 in total

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