Volume 43 Issue 1
Feb.  2025
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Article Navigation >  Journal of Transport Information and Safety  > 2025  >  43(1): 15-30
MA Yuhan, YANG Peijie, XUE Jie, ZHENG Yuan, YANG Hao, HU Hao. Research Hotspots and Development Trends of Container Multimodal Transport in China[J]. Journal of Transport Information and Safety, 2025, 43(1): 15-30. doi: 10.3963/j.jssn.1674-4861.2025.01.002
Citation: MA Yuhan, YANG Peijie, XUE Jie, ZHENG Yuan, YANG Hao, HU Hao. Research Hotspots and Development Trends of Container Multimodal Transport in China[J]. Journal of Transport Information and Safety, 2025, 43(1): 15-30. doi: 10.3963/j.jssn.1674-4861.2025.01.002
shu

Research Hotspots and Development Trends of Container Multimodal Transport in China

doi: 10.3963/j.jssn.1674-4861.2025.01.002
  • 1.

    School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

  • 2.

    Key Laboratory of Safety and Risk Management on Transport Infrastructures of Ministry of Transport, Southeast University, Nanjing 210008, China

  • Received Date: 2024-08-18
    Available Online: 2025-06-27
    Abstract
  • Amid accelerating globalization of international trade, container multimodal transport has emerged as the dominant mode of international cargo movement. Rising market diversification and technological innovations now drive transformative opportunities for container multimodal transport in China. To systematically summarize existing research, 475 Chinese and English articles (from 1st January 2000 to 10th July 2024) are retrieved from the China National Knowledge Infrastructure (CNKI) core database. Using CiteSpace visualization and literature synthesis, publication patterns, research status, key themes, and development trends are evaluated in China's container multimodal transport research. Key findings reveal four research domains: novel container designs, path optimization algorithms, green logistics systems, and digital platforms development. Critical challenges persist, including fragmented automation coverage, limited smart technology adoption, and inadequate algorithm validation in complex operational scenarios. Additional constraints involve underdeveloped green energy integration, incomplete carbon taxation frameworks, and cybersecurity risks in data-sharing platforms. Emerging trends highlight multidimensional innovation focusing on: AI-driven dynamic response systems for autonomous decision-making, adaptive algorithms for multi-scenario process optimization, blockchain-enabled smart contract solutions, and synergistic green energy-grid integration strategies, etc.

     

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