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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 role of logistics service provider (LSP) is essential for efficient logistics service quality (LSQ) and supply chain management, especially in multimodal transport. Multimodal transport routes that use the Trans-Siberian Railway (TSR) play an important role in the supply chains of Northeast Asia. This paper aims to identify current conditions of TSR LSQ and propose improvements to enhance the competitiveness of traditional routes. Therefore, this study sheds light on and provides recommendations for various managerial strategies to LSPs in the context of the TSR. This study utilizes Importance-Performance Analysis (IPA) to measure levels of importance and performance of the logistics service of LSPs that provide multimodal transport services via the TSR from South Korea to Europe. This study identifies capabilities on the basis of five criteria (price, timeliness, reliability, equipment systems, and customer service) from a customers’ perspective. The results of the research indicate that operational improvements should be considered to activate TSR multimodal transport for northern logistics routes from the perspective of Korean shippers. Specific findings show that balanced development strategies are needed for logistics routes that have not yet been significantly activated, while implying that logistics costs could be reduced initially to satisfy shippers. This study presents an operational strategy for LSPs using the TSR in northern logistics through IPA methods. Furthermore, this research can help policymakers propose specific policies to revitalize the northern logistics of Korean logistics companies and to provide incentive supports for shippers.

Considering the proliferation of free trade agreements (FTAs) worldwide, this study develops and empirically tests a conceptual model to explain the impact of CEO attitudes on the intention of exporting firms to utilize FTA preferential tariffs. Based on a survey of 221 exporting small and medium-sized enterprises in South Korea, this study employed partial least squares structural equation modelling to test the hypotheses. Results show that perceived usefulness and organizational learning partially mediate the relationship between CEO attitudes and intention to use FTA schemes. This study deepens our understanding on the firm’s internal process for utilizing FTA preferential tariffs.

This study examines various artificial intelligence (AI) models for predicting financially distressed firms with poor profitability (“Zombie firms”). In particular, we adopt the Explainable AI (“XAI”) approach to overcome the limitations of the previous AI models, which is well-known as the black-box problem, by utilizing the Local Interpretable Model-agnostic Explanations (LIME) and the Shapley Additive Explanations (SHAP). This XAI approach thus enables us to interpret the prediction results of the AI models. This study focuses on the Korean sample from 2019 to 2023, as it is expected that the COVID-19 pandemic increases the number of zombie firms. We find that the XGBoost model based on a boosting technique has the best predictive performance among several AI models, including the traditional ones (e.g. the logistic regression). In addition, by using the XAI approach, we provide visualized interpretations for the prediction results from the XGBoost model. The analysis further reveals that the return on sales and the selling, general and administrative costs are the most impactful variables for predicting zombie firms. Overall, this study focusing on several AI models not only shows the improvement for the prediction of zombie firms (relative to the traditional models) but also increases the reliability of the prediction results by adopting the XAI approach, providing several implications for market participants, such as financial institutions and investors.

Competition among seaports is rapidly increasing due to various factors such as the global recession, resurgence of COVID-19, tight environmental regulations of IMO, sharp rise in ocean freight charges, increasing global uncertainties and growth in ship sizes. It is essential to have precise knowledge of shipping companies' port selection factors to secure the competitive advantage of seaports. This study aims to empirically analyze recent changes in the importance of port selection factors.

By employing a longitudinal study, this study conducted the t-test analysis. The first survey was conducted from January 2005 to April 2005. Then, the second survey was conducted in May 2021.

First, the importance of port facilities (berth length and the number of berths, shed and terminal areas, possession of adequate equipment and maximum berth size) increased significantly. Second, while ship and cargo safety were the critical port service factors in previous studies, speed, flexibility and reliability for handling cargo and berthing schedule were found to be crucial in this study. Third, the importance of ship arrival/departure frequency, route diversity and ship arrival/departure information systems increased when shipping companies selected the port.

This study has academic significance in that it reveals the changing importance of port selection factors in the 2020s and has taken the form of a longitudinal study on the importance of port selection factors from 2005 to 2021, moving beyond the cross-sectional approach. This study can provide valuable insights into and implications for port policymakers and managers when developing and formulating port policies and strategies.

This paper aims to identify the factors that experts consider important for the effective operation of multimodal transport using the Trans-Siberian Railway (TSR) in the Russian Far East and to also establish operational strategies that enable Korean logistics companies to use TSR efficiently for multimodal transportation.

A total of 65 questionnaires were distributed to predominantly Korean logistics companies/shippers with experience in TSR and 19 replies were received. The majority of the respondents are senior executives with at least 10 years of work experience. To identify the factors and present strategies, this study applied the strengths, weaknesses, threats and opportunities -fuzzy analytic hierarchy process (FAHP) method, which is based on complex multiple-criteria decision-making (MCDM) that facilitates decision-makers in considering an operational strategy by calculating the importance of input factors.

Results from the FAHP indicate that the Strengths is the main factor affecting TSR multimodal transport decisions, followed by the Threats, Opportunities and Weakness factors. In terms of rank, reduction of transportation distance and time are determined as the most crucial factor from the perspective of Korean logistics companies, followed by the northern logistics development plan, the Russian Government's willingness to the development plan, political instability and possible linkages with the Korean ports.

Through a hybrid MCDM analysis of Korean logistics companies, three operational strategies were proposed: foreign direct and small investments in the Russian Far East, Korean logistics companies implementing a cold-chain logistics service in the fishery industry and a government-led “Block Train Integration System” to secure the minimum threshold volume of cargo for small and medium-sized companies.