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The Incheon Region has numerous assets that fall within a Pentaport model.' These include the Incheon International Airport, the Port of Incheon, a coastal industrial park, free economic zones, a leisure port, and Songdo new town designed to be the future Silicon Valley of Korea. This paper looks at how Northeast Asia trade flows between China and Korea might be enhanced by application of the Pentaport model in making the Incheon region a North East Asian Hub. It looks also at their trade and logistics systems as well as their water borne commerce. It proposes an integrated transportation system for the Yellow Sea Region being beneficial to the economies of the Northeast Asia. It also stresses that innovative technologies for ships, terminals and cargo handling systems should be introduced to develop a competitive short sea shipping system in the region and cooperation among the regional countries will be essential to achieve the final goal. The potential of methods of container shipping is discussed as it might apply to short sea shipping in the Yellow Sea Region that could greatly facilitate Incheon's situation with respect to the broader region in application of the Pentaport model.

This paper analyzes the logistics patterns of Korea to elaborate the strategies of Korean Free Economic Zones (FEZs) in relation to Northeast Asian logistics hubs. As the surface transportation of Korea, China and Japan, is cut off by geographical factors and by political border lines, this paper confines the analysis scope to air and maritime transportation.

From the analysis of air and maritime transportation in Northeast Asian region, this paper tries to understand the cargo flow from and to Korean airports and ports by region and by commodity types, and thereby, to identify the main counterpart regions of trade by commodity types and by modes. The policy implications for the development strategy of Korean FEZs (Incheon, Busan, and Gwangyang) are described from those analyses.

This paper investigates a retrospective on the Journal of Derivatives and Quantitative Studies (JDQS) on its 30th anniversary based on bibliometric. JDQSs yearly publications, citations, impact factors, and centrality indices grew up in early 2010s, and diminished in 2020. Keyword network analysis reveals the JDQS's main keywords including behavioral finance, implied volatility, information asymmetry, price discovery, KOSPI200 futures, volatility, and KOSPI200 options. Citations of JDQS articles are mainly driven by article age, demeaned age squared, conference, nonacademic authors and language. In comparison between number of views and downloads for JDQS articles, we find that recent changes in publisher and editorial and publishing policies have increased visibility of JDQS.