Review of multimodal transport research based on bibliometrics

XU Zhi-gang; SHEN Dan-dan; GAO Ying; ZHAO Xiang-mo; YANG Min; YANG Xiao-guang; DONG Chun-jiao; YANG Zhong-zhen

doi:10.19818/j.cnki.1671-1637.2025.02.003

Volume 25 Issue 2

Apr. 2025

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XU Zhi-gang, SHEN Dan-dan, GAO Ying, ZHAO Xiang-mo, YANG Min, YANG Xiao-guang, DONG Chun-jiao, YANG Zhong-zhen. Review of multimodal transport research based on bibliometrics[J]. Journal of Traffic and Transportation Engineering, 2025, 25(2): 37-60. doi: 10.19818/j.cnki.1671-1637.2025.02.003

Citation:

XU Zhi-gang, SHEN Dan-dan, GAO Ying, ZHAO Xiang-mo, YANG Min, YANG Xiao-guang, DONG Chun-jiao, YANG Zhong-zhen. Review of multimodal transport research based on bibliometrics[J]. Journal of Traffic and Transportation Engineering, 2025, 25(2): 37-60. doi: 10.19818/j.cnki.1671-1637.2025.02.003

Citation:

XU Zhi-gang, SHEN Dan-dan, GAO Ying, ZHAO Xiang-mo, YANG Min, YANG Xiao-guang, DONG Chun-jiao, YANG Zhong-zhen. Review of multimodal transport research based on bibliometrics[J]. Journal of Traffic and Transportation Engineering, 2025, 25(2): 37-60. doi: 10.19818/j.cnki.1671-1637.2025.02.003

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Review of multimodal transport research based on bibliometrics

doi: 10.19818/j.cnki.1671-1637.2025.02.003

1.
School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China
2.
School of Transportation, Southeast University, Nanjing 210096, Jiangsu, China
3.
College of Transportation, Tongji University, Shanghai 201804, China
4.
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
5.
Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, Zhejiang, China

Funds:

National Natural Science Foundation of China 52142201

Natural Science Basic Research Program of Shaanxi Province 2023-JC-JQ-45

Fundamental Research Funds for the Central Universities 300102242202

More Information

Corresponding author: ZHAO Xiang-mo (1966-), male, professor, PhD, E-mail: xmzhao@chd.edu.cn
Received Date: 2024-10-02
Publish Date: 2025-04-28

Abstract

Abstract

To comprehensively understand the research progress in the field of multimodal transport, bibliometric methods was adopted to systematically retrieved relevant literature from the WOS core database and the China National Knowledge Infrastructure (CNKI) database from 1990 to 2024, totaling 32111 articles, involving 2 244 authors and 1 422 keywords. Through scientific knowledge mapping, the distribution of literatures, publishing countries, research institutions, and authors were systematically analyzed and visualized. Keyword co-occurrence maps and clustering maps were used to reveal the research hotspots in this field. Emergent term analysis was conducted to predict future research directions. Research results show that multimodal transport research has gone through three stages: slow growth, steady growth, and rapid growth. The hotspots are concentrated in the analysis, planning and design, operation, and logistics of multimodal transport systems. Specifically, these include: the supply-demand relationship of multimodal transport systems, network models, the relationship between travel behavior and land use, multimodal transport network layout optimization, regional connectivity and interoperability improvement, seamless connection and efficient operation of multiple transport modes, and logistics network, transportation path optimization, and freight flow efficiency improvement. Currently, the research focuses of domestic and international scholars are highly overlapping but still differ. Domestic scholars focus more on the strategic development, structural optimization, comprehensive planning, and national urgent scenario research of multimodal transport. In contrast, international research focuses more on multimodal transport theory and the application of emerging technologies. In the future, with the development of artificial intelligence, big data, blockchain, and digital twins, multimodal transport research will move towards more integrated, three-dimensional, digital, networked, shared, and low-carbon, to achieve efficient utilization of transport spatiotemporal resources, energy, and computing power. Cross-industry, cross-field, cross-department, and cross-level collaboration and coordination will become key to driving the continuous development of multimodal transport research. This will promote resource integration and optimization, helping to build an efficient, intelligent, safe, and environmentally friendly multimodal transport system.
- multimodal transport,
- bibliometric analysis,
- review,
- map of scientific knowledge,
- visual analysis,
- research hotspot,
- development trend

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References(123)

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Review of multimodal transport research based on bibliometrics

doi: 10.19818/j.cnki.1671-1637.2025.02.003

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Review of multimodal transport research based on bibliometrics

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