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Coauthorship network in transportation research

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  • Sun, Lijun
  • Rahwan, Iyad

Abstract

The field of transportation research has been accelerating in the last decade. In this paper, we examine the structure of scientific collaboration in transportation research by building a coauthorship network using publication metadata from 22 transportation journals. In this network, a vertex represents a researcher and an edge represents the collaboration (coauthorship) between a pair of researchers. To build an accurate network, we propose and apply an efficient author name correction algorithm. The obtained network provides us with a tool to understand patterns of collaborations in transportation research. The results show an increasing trend of collaboration over the studied period (1990–2015), but different journals exhibit different patterns. We characterize the structural properties of this network and compute several centrality measures to quantify the performance/impact of researchers and their collaborations in the research community. This study could serve as a tool to qualitatively and quantitatively understand scientific collaborations in transportation research.

Suggested Citation

  • Sun, Lijun & Rahwan, Iyad, 2017. "Coauthorship network in transportation research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 135-151.
    • Handle: RePEc:eee:transa:v:100:y:2017:i:c:p:135-151
    DOI: 10.1016/j.tra.2017.04.011
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    Cited by:

    1. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.
    2. Nadia Karina Gamboa-Rosales & José María Celaya-Padilla & Ana Luisa Hernandez-Gutierrez & Arturo Moreno-Baez & Carlos E. Galván-Tejada & Jorge I. Galván-Tejada & Edgar González-Fernández & Hamurabi Ga, 2020. "Visualizing the Intellectual Structure and Evolution of Intelligent Transportation Systems: A Systematic Analysis of Research Themes and Trends," Sustainability, MDPI, vol. 12(21), pages 1-30, October.
    3. Kiran Sharma & Parul Khurana, 2021. "Growth and dynamics of Econophysics: a bibliometric and network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4417-4436, May.
    4. Modak, Nikunja M. & Merigó, José M. & Weber, Richard & Manzor, Felipe & Ortúzar, Juan de Dios, 2019. "Fifty years of Transportation Research journals: A bibliometric overview," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 188-223.
    5. Xiaofeng Ji & Haotian Guan & Mengyuan Lu & Fang Chen & Wenwen Qin, 2022. "International Research Progress in School Travel and Behavior: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(14), pages 1-25, July.
    6. Sun, Yanshuo & Kirtonia, Sajeeb, 2020. "Identifying regional characteristics of transportation research with Transport Research International Documentation (TRID) data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 111-130.
    7. Chen, Shukai & Meng, Qiang & Choi, Tsan-Ming, 2022. "Transportation research Part E-logistics and transportation review: 25 years in retrospect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    8. Jiang, Chenming & Bhat, Chandra R. & Lam, William H.K., 2020. "A bibliometric overview of Transportation Research Part B: Methodological in the past forty years (1979–2019)," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 268-291.
    9. Tanrıverdi, Gökhan & Bakır, Mahmut & Merkert, Rico, 2020. "What can we learn from the JATM literature for the future of aviation post Covid-19? - A bibliometric and visualization analysis," Journal of Air Transport Management, Elsevier, vol. 89(C).

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