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Railways Transport Infrastructures for Supporting Tourism: A Bibliometric Analysis

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Computational Science and Its Applications – ICCSA 2023 Workshops (ICCSA 2023)

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Abstract

In this paper, we present a bibliometric analysis of the Railway Transport Infrastructure model for supporting tourism. We identify the its research evolution for past decade, including; source, document type, journal name, publisher name, topic trends, and author collaborations. Bibliometric analysis was used to analyze 48 articles published from 2013 to 2023. Railway Transport Infrastructure for Tourism is the main keyword used in article titles, abstracts, and keywords to get metadata retrieved from the Scopus database. The tools used in this bibliometric analysis are Harzing's Publish or Perish to extract data from the Scopus database and VoS Viewer for data visualization and further used for citation and metric analysis. The results of this study show that most articles related to railway transport infrastructure for tourism are published in scientific journals, compared to others, where they received the highest citations. Based on network visualization, the most dominant term is tourism development as the key term related to several other issues of railway transport, tourism, transport infrastructure, and economic growth. Meanwhile, when viewed from the overlay visualization, the dominant keywords are transportation infrastructure, data panels, social networks, air transportation, high speed rail, and economic growth. Based on the findings presented in network visualization and overlay visualization, it can be concluded that articles with the topic railway transport infrastructure for tourism have not been widely studied, so they can be used as an interesting keyword for further research.

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Acknowledgment

This research is fully supported by Ambarrukmo Tourism Institute, Yogyakarta, Indonesia.

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Rahmawati, E., Hendratono, T., Sugiarto, S., Pradini, G., Herawan, T. (2023). Railways Transport Infrastructures for Supporting Tourism: A Bibliometric Analysis. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14110. Springer, Cham. https://doi.org/10.1007/978-3-031-37123-3_33

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  • DOI: https://doi.org/10.1007/978-3-031-37123-3_33

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