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Analyzing Sustainability Literature in Maritime Studies with Text Mining

Sung-Ho Shin (), Oh Kyoung Kwon (), Xiao Ruan (), Prem Chhetri (), Paul Tae-Woo Lee () and Shahrooz Shahparvari ()
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Sung-Ho Shin: Department of International Logistics, Pyeongtaek University, Pyeongtaek 17869, Korea
Oh Kyoung Kwon: Graduate School of Logistics, Inha University, Incheon 22212, Korea
Xiao Ruan: Ocean College, Zhejiang University, Zhoushan 316012, China
Prem Chhetri: School of Business IT and Logistics, College of Business, RMIT University, Melbourne 3001, Australia
Paul Tae-Woo Lee: Ocean College, Zhejiang University, Zhoushan 316012, China
Shahrooz Shahparvari: School of Business IT and Logistics, College of Business, RMIT University, Melbourne 3001, Australia

Sustainability, 2018, vol. 10, issue 10, 1-19

Abstract: Since the world’s first Earth Summit in Rio de Janeiro in 1992, sustainability has become a focal point of significant debate for industry, government, and international organizations. As a result, research on sustainability of maritime logistics is on the rise, yet fragmented in terms of conceptual development, empirical testing and validation, and theory building. The aim of this paper is therefore two-fold: the first aim is to present a literature review of key journal articles in the field of maritime studies published between 1993 and 2017 using a technique of topic modelling; and the second is to provide future research directions with respect to major topics, themes and co-authorship patterns. Mapping and consolidation of sustainability issues are achieved by conducting a generative probabilistic text-mining technique, called latent Dirichlet allocation (LDA), for latent data discovery and relationships among text document data. Moreover, bibliometric analysis is conducted to visualize the landscape of sustainability research. Based on the results, a new intellectual structure of sustainability research is created, the underlying themes are identified, key trends and patterns are extracted and future research development trajectories are mapped for the field of maritime studies.

Keywords: sustainability; maritime studies; topic modeling; Latent Dirichlet Allocation; LDA; research trend (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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