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Research Context and Prospect of Green Railways in China Based on Bibliometric Analysis

Author

Listed:
  • Weiya Chen

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Xiaoqi Shi

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Xiaoping Fang

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Yongzhuo Yu

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Shiying Tong

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

Abstract

The CiteSpace bibliometric software was used to quantitatively analyze the research papers on green railways retrieved from the China National Knowledge Infrastructure (CNKI) database during 1985–2021. Combined with content association analysis, the development stages, frontier hotspots, and evolutionary trends of green railway research in China were summarized in the Chinese context. The results show that in the past 36 years, China’s green railway research has experienced four main stages: the emerging stage (1985–1997), the horizontal expansion stage (1998–2010), the vertical deepening stage (2010–2015), and integrated expansion stage (2016–present). The research topics emerging in the four stages are green design and green construction, green channel and green logistics, energy conservation and emission reduction and green evaluation, multimodal transportation, and green development. In general, the research topics are diversified, but green construction of railway infrastructures and green manufacturing of railway equipment have been the research hotspots all the time. Both external and internal paths drive the transmutation of academic frontiers, and the push effect of the external path is more evident than the internal path. Interdisciplinary integration and innovation gradually become a new force to promote green railway research. As the railway development slowly enters a “big operation era”, it can be inferred that the development trend of green railway research could throw light on the following three areas: from the research perspective and topics, it should be based on a framework of life cycle management to explore, systematically and deeply, the correlation and integration of railway green design, green construction, green operation and maintenance; in terms of the research content, more focus should be on new theories, new methods, and new technologies of railway green operation and green maintenance on the basis of railway green design, construction, and manufacturing research, such as railway green operation strategies and evaluation systems and green transportation organization theories and methods; from innovation paths, academic progress still needs both external and internal paths, interdisciplinary integration and innovation as the primary internal driving force to promote green railway research, and more focus on the use of big data and artificial intelligence and other technologies to innovate green railway development.

Suggested Citation

  • Weiya Chen & Xiaoqi Shi & Xiaoping Fang & Yongzhuo Yu & Shiying Tong, 2023. "Research Context and Prospect of Green Railways in China Based on Bibliometric Analysis," Sustainability, MDPI, vol. 15(7), pages 1-12, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:5773-:d:1107875
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    References listed on IDEAS

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    1. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Huchang Liao & Ming Tang & Li Luo & Chunyang Li & Francisco Chiclana & Xiao-Jun Zeng, 2018. "A Bibliometric Analysis and Visualization of Medical Big Data Research," Sustainability, MDPI, vol. 10(1), pages 1-18, January.
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    Cited by:

    1. Juan Hao & Xinqin Gao & Yong Liu & Zhoupeng Han, 2023. "Acquisition Method of User Requirements for Complex Products Based on Data Mining," Sustainability, MDPI, vol. 15(9), pages 1-19, May.
    2. Weiya Chen & Yongzhuo Yu & Xiaoping Fang & Ziyue Yuan & Shiying Tong, 2023. "Using Mixed Methods to Identify Evaluation Indicators for Green Railway Transportation Operations in China," Sustainability, MDPI, vol. 15(24), pages 1-21, December.
    3. Kristina Čižiūnienė & Jonas Matijošius & Edgar Sokolovskij & Justė Balevičiūtė, 2024. "Assessment of Implementing Green Logistics Principles in Railway Transport: The Case of Lithuania," Sustainability, MDPI, vol. 16(7), pages 1-24, March.

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