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This paper presents a case study on the problem of loading air containers in air express carriers motivated from DHL and Air Hong Kong. The problem is to determine the containers to be loaded and the locations of the loaded containers in an aircraft while maintaining stability of the aircraft. The objective of the problem is to maximize the revenue obtained from delivering containers. We present an integer programming model to represent and optimally solve the problem. Computational experiments done on a number of randomly generated test instances show that the integer program can be a viable tool for generating loading plans in the companies since optimal or near-optimal solutions for the test instances are obtained within a reasonable amount of computation time.

The restructuring of shipping and shipbuilding companies in the midst of rapidly shrinking global shipping demand has become a prominent issue in Korea. In shipping finance, loan syndication featuring many creditors surges as the preferred option. However, increasing the numbers of creditors in the syndicate results in two opposite effects. First is the beneficial effect from their enhanced monitoring power. On the other hand, there is the adverse effect resulting from increased difficulty in coordination when syndicate members increase, particularly in bankruptcy. Our aim of this paper is to analyze the role of finance in the shipping and shipbuilder markets, and determine the theoretical optimal number of creditors for the shipping finance syndicate based on Bolton and Scharfstein (1996). The two issues above result from moral hazard and non-verifiability: coordination among many creditors for collection of bonds in case of default, and the enhancement of monitoring private benefit exploitation by the ship-owner during default. Considering the two conflicting forces result from an increase in creditor membership, we draw conclusions on determining the optimal number of creditors by considering trade-offs between these two factors: More creditors are preferred when the monitoring effect dominates. Otherwise, less creditors are preferred.

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.