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Importance rankings of nodes in the China Railway Express network under the Belt and Road Initiative.
Zhang, Xu; Zhang, Wei; Lee, Paul Tae-Woo.
  • Zhang X; School of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian, China.
  • Zhang W; Department of Maritime and Logistics Management, National Centre for Ports and Shipping, Australian Maritime College, University of Tasmania, Launceston, Australia.
  • Lee PT; Ocean College, Zhejiang University, Zhoushan, China.
Transp Res Part A Policy Pract ; 139: 134-147, 2020 Sep.
Article en En | MEDLINE | ID: mdl-32834668
ABSTRACT
China Railway Express (CR express) refers to the regular container trains transporting between China and European countries under the Belt and Road Initiative (BRI). This paper aims to conduct the systematic and in-depth research on the importance ranking of logistics nodes across the complex CR express network from China's national plan of the BRI perspective, with consideration of the connectivity between the 21st-Century Maritime Silk Road (MSR) and the Silk Road Economic Belt (SREB). In doing so, first, it sets up the complex network in the CR express transport. Second, based on the restraint coefficients in the theory of structural hole such as network scale, efficiency, grading and clustering co-efficiency, this paper applies the Multiple Attribute Decision Making (MADM) model in association with algorithm development in calculating the importance of the CR express nodes including both inland nodes and seaport nodes. The paper has three-fold contributions. In theory, it confirms the accuracy and practicability of the structural hole theory in the importance ranking of nodes in the complex network. In practice, it identifies important logistics nodes of CR express network across the BRI. Further, the findings in the paper contribute to optimising the structure of CR express transport and improving its network stability.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Año: 2020 Tipo del documento: Article