期刊
TRANSPORT POLICY
卷 102, 期 -, 页码 11-24出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.tranpol.2020.12.013
关键词
Maritime transport; Shipping; Port; Text mining; Structural topic model; Research trends
资金
- National Natural Science Foundation of China (NSFC) [72001123, 72031005]
- Key project of Philosophy and Social Science Research of Ministry of Education, PRC [20JZD016]
- Center for Smart Logistics and Supply Chain Systems, Tsinghua University, China [THUCSL20182911756-010]
Maritime transport is crucial for global trade and has seen a shift in research focus from regulatory aspects to efficiency, integration, and sustainability. The use of a structural topic model has helped identify key research themes and trends in the maritime literature, aiding researchers, funding groups, and policymakers in making informed decisions.
Maritime transport is considered as the lynchpin of global trade. In the past decades, a large number of academic articles in the maritime transport field have been published. This study aims to provide a comprehensive review of the development of maritime transport research. A structural topic model (STM) is adopted to analyze the research themes and trends in the maritime literature. STM is a text mining-based methodology to uncover main topics from large-scale unstructured textual data. In total, 3199 articles published between Jan 1991 and Aug 2020 were collected and analyzed. The results show that the major academic concerns of maritime transport are related to port management, container operations and liner shipping management. The overall research trends have shifted from regulations and policy management to efficient, integrated and sustainable maritime transport over the past few decades. The main research topics and emerging trends discovered from STM can facilitate researchers, funding groups and policymakers for identifying contemporary research issues and making more informed decisions.
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