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This study aims to examine the trend of industrial competition between the US and China, which is the most crucial determinant in the future development of the global economy. For decades, the global economy has strengthened the global production network based on the division of labor between countries. Thus, the ripple effect of competition between the two countries should be analyzed in terms of the global production network. Therefore, this study uses the product space model, which explains the development process of industries with comparative advantage by country. We constructed the model based on the products of HS 4-digit code for the 2010–2019 period. The analysis results on the trend of the industrial competitiveness of major countries are as follows. First, the current industrial competitiveness of China is concentrated on low-tech industries. In the case of high-tech items, China shows a tendency of lower export sophistication compared to major manufacturing powerhouses such as Germany, the US, Japan, and Korea. Second, with respect to the possibility of a future industrial structure upgrade evaluated by density, the trend of China overtaking other manufacturing powerhouses is observed. As implied by the product space model, the advancement of the industrial structure through active participation in international trade enhances the industrial competitiveness. Therefore, the outcome of US-China industrial competition depends on who ensures more openness and industrial complexity.

The air transportation industry is one big network that is expected to grow continuously, and Asia-Pacific is the fastest growing region as of 2018 data. We apply weighted network analysis to explore the key network characteristics of the Asian international passenger aviation market in 2014 and 2018. For the analysis, networks are constructed based on international passengers' origin-destination pair data from 28 Asian airlines in 2014 and 2018. Previously published social network analysis (SNA) on the air transportation network largely used unweighted centrality metrics, whereas the actual situation is a weighted network. We implement Mean Associations (MA), Triangle Betweenness Centrality (TBC), and Weighted PageRank (WPR), as new weighted centrality metrics, to effectively reflect actual passenger traffic among airports beyond simple connections. Our weighted network analysis indicates that SIN, ICN, HKG, NRT, MNL, BKK, TPE, HND, PEK, and KUL are the top-ranked hub airports, followed by SGN, PVG, CAN, DEL, SYD, KIX and CGK, and that the low-cost carriers have almost fully developed a ‘hub-and-spoke’ structure over the 4-year study period and are increasing their impact on the centrality of airports in the region.

In today’s multi-channel distribution environment, it is crucial for the competitiveness of retail stores and companies to improve efficiency of dedicated logistics centers (DLCs) servicing types of retail outlets such as large retail-stores, super supermarkets, and convenient stores. This paper derives efficiency improvement strategies for DLCs through efficiency analyses. To this end, this paper empirically analyzes the efficiency of DLCs by applying DEA (data envelopment analysis) approaches using real data from a Korean distribution company. In detail, this paper analyzes operations, finance, and service efficiencies of DLCs and performs a comparison analysis on the efficiency between DLCs. Finally, this paper discusses the analysis results considering the DLCs’ characteristics and derives managerial and operational implications.

Owing to growing economic growth in tandem with regional economic developments on the route connecting Asia and sub-Saharan Africa (SSA), several countries in the SSA region such as South Africa have been developing container ports. This paper analyzes potential trunk line routes and transshipment flows that could be captured by potential hub ports in the SSA region. To this end, integer programing models are developed to represent liner shipping networks in the SSA region and a wide variety of numerical experiments based on realistic data are conducted for the SSA-Europe and SSA-Asia trade routes. This paper draws various meaningful policy and managerial implications through scenario analyses such as the effects of network evolution, different vessel sizes and speeds, carbon taxes and insights in association with the 21st Century Maritime Silk Road initiated by China.

This paper aims to provide a practical method for forecasting potential container cargo volume that can be induced by a port development project on a container transport network by combining port choice and an autoregressive integrated moving average (ARIMA) model. The entrance channel improvement plan for Incheon New Port in South Korea is used as a case study. Based on the stated preference data collected from domestic shippers, a discrete choice analysis is performed to estimate the future market share of three major ports in South Korea: Busan, Gwangyang, and Incheon. The estimated market share of Incheon New Port is used to forecast its future container volume derived by the ARIMA model and the potential port development scenarios.

This paper discusses a case of truck sharing as an application of the sharing economy. This case study examines a real mixed feed company with multiple factories. In this company’s operation, bulk trucks located in a factory had not previously been shared for delivery with other factories to their pre-assigned customers of stock farms. Therefore, this paper suggests a new delivery system that facilitates truck-sharing and analyzes its effects on the transport cost and trucks’ CO2 emissions. To this end, this paper develops vehicle routing models to represent the current delivery practice and the new truck-shared delivery (TSD). In addition, models are developed for a carbon control policy of an emission trading scheme (ETS) and the effects of the ETS on truck-sharing are investigated. Numerical analysis is conducted to identify the effects of the TSD and the carbon control policy and draw practical implications.

Owing to high fuel costs and environmental regulations, the optimization of ship speed to minimize fuel consumption and reduce carbon emissions has become a hot issue in the maritime industry. In this paper, we study the sailing speed optimization problem for a ship operating on a route having a specified sequence of calling ports with time windows for calling time. The considered problem can be formulated as a non-linear program. We derive the intrinsic properties of the problem and develop an optimal algorithm based on the properties. Computational experiments show that the developed algorithm in this paper is efficient in finding an optimal solution.

This article analyzes an intermodal transportation network for international container cargoes in Korea. The actual transportation situation in Korea is formulated by a linear programming model. The model is validated first by comparing the model output with actual performance, and then the model is extended by incorporating various externalities arising from inland transport modes such as air pollution, congestion, accidents, noise pollution, and wear and tear. Moreover, the model is extended for assessing the effects of complying with carbon taxation and emission trading schemes, which loom large in international shipping communities. Test results of the models using the data obtained from reliable sources are presented and policy directions are discussed from an environmental perspective.

This paper provides an algorithm to minimize the fixed ordering, purchase, and inventory-carrying costs associated with bunker fuel together with ship time costs; and environmental costs associated with greenhouse gas emissions. It determines the optimum ship speed, bunkering ports, and amounts of bunker fuel for a given ship’s route. To solve the problem, we use an epsilon-optimal algorithm by deriving a property. The algorithm is illustrated by applying it to typical sample data obtained and the effects of bunker prices, carbon taxes, and ship time costs on the ship speed are analyzed. The results indicate that the ship speed and CO2 emissions are highly sensitive to the factors considered.

This paper presents a case study on the problems which result when loading air containers onto DHL and Air Hong Kong air express carriers. Problems often arise when trying to determine which containers should be loaded and where the containers should be located in an aircraft in order for it to maintain stability. The objective of this activity is to maximize the revenue obtained from delivering containers. We will present an integer programming model which will attempt to optimally solve the problem. Computational experiments which have been done on a number of randomly generated test instances show that the integer programming model can be a viable tool for generating loading plans within the companies since optimal or near-optimal solutions were obtained during the test instances within a reasonable amount of computation time.

The strategic location of city logistics facilities may help to establish more efficient urban logistics systems, reduce social and environmental costs of urban freight transport, and improve urban traffic conditions. In addition, it may allow a number of shippers or freight carriers to jointly operate freight vehicles and terminals or information systems while allowing them to have the capability to provide higher levels of services to their customers. This paper considers the problem of selecting a location for a city logistics facility while considering linguistic factors. This paper identifies the important factors in the selection of a location for a city logistics facility by performing a case study which applies the analytic hierarchy process method on data from Chongqing, China. The optimal location in Chongqing is then determined by using the fuzzy synthetic evaluation method. The results of this paper are expected to help municipal governments select appropriate locations for city logistics facilities and quantify the advantages and disadvantages of alternative locations.

Dynamic lot sizing is the problem of determining the quantity and timing of ordering items while satisfying the demand over a finite planning horizon. This paper considers the problem with two practical considerations: minimum order size and lost sales. The minimum order size is the minimum amount of items that should be purchased and lost sales involve situations in which sales are lost because items are not on hand or when it becomes more economical to lose the sale rather than making the sale. The objective is to minimize the costs of ordering, item , inventory holding and lost sale over the planning horizon. To solve the problem, we suggest a heuristic algorithm by considering trade-offs between cost factors. Computational experiments on randomly generated test instances show that the algorithm quickly obtains near-optimal solutions.

This paper considers a multimodal transportation problem, which is the problem of determining the transportation flow, i.e. volume of container cargoes, and the transportation mode in each trade route, for the objective of minimizing the sum of shipping and inland transportation costs. The problem takes account of two restrictions: maximum cargo volumes capacitated at each seaport and maximum number of vehicles available at each transportation mode. To solve optimally the problem, this paper employs a mixed integer programming, which is an operations research technique. A case study is performed on the container cargo data in Korea and we draw several implications to improve efficiency in the transportation of international trade cargoes in Korea.

This paper addresses the problem of determining the ship speed, fleet size, and chartered ship number subject to environmental regulations consisting of a carbon tax and an emission trading scheme. The objective of the problem is to minimise bunker consumption cost, ship operating cost, ship charterage and either the carbon tax or the revenue/cost of selling/purchasing CO2 emissions permits. We formulate the problems as non-linear programmes by considering the two regulations independently. This study also suggests Lagrangian heuristics to solve the problems. A case study is performed to evaluate the applicability of the heuristics.