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  • 标题:Keyword network analysis: Uncovering research trends on the Northern Sea Route
  • 本地全文:下载
  • 作者:Thi Le Hang Nguyen ; Sung-Hoon Park ; Gi-Tae Yeo
  • 期刊名称:The Asian Journal of Shipping and Logistics
  • 印刷版ISSN:2092-5212
  • 出版年度:2021
  • 卷号:37
  • 期号:3
  • 页码:231-238
  • 语种:English
  • 出版社:Elsevier
  • 摘要:The Northern Sea Route (NSR) has gradually become viable because of sea ice melting in the Artic. There is a large and diverse body of research on the NSR, investigating aspects such as weather, the environment, legal security, infrastructure and technologies, shipping transportation, and economic issues. However, there has been scant research carried out from a macroscopic perspective on NSR research trends. The purpose of this study is to analyze the trends in research about the NSR by applying a social network analysis. By collecting keywords from academic papers on the NSR, a network of keywords and two indexes (degree centrality and betweenness centrality) are accessed and analyzed. The results show that the trends can be divided into three periods (1899–1999, 2000–2009, 2010–2019). Throughout all periods, the issue of climate change causing the ice in the Arctic to melt has been a consideration for many scholars. In addition, “national security” and “oil exploitation” were important keywords in the first period. In the second period (2000–2010), in addition to words related to the environment, such as “sea ice” and “climate change,” the term “ocean transport” appears and becomes a central topic of research. This is because when the NSR has a non-icy period, ocean transport through the NSR can be deployed. The research trends become obvious in the third period (2011–2019) with two primary research areas: climate change and shipping area, which accurately measure the benefit and cost. This paper shows the importance of the NSR, reviews the main research topics involving the NSR, and informs researchers and authorities as to the trends in academic research on the NSR.
  • 关键词:Northern Sea Route;Research trend;Social network analysis;Keyword network;Ocean transport
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