This paper focuses on a container transhipment hub in South Asia (namely, Colombo port, Sri Lanka) and its competitive situation, by applying a model to predict global container movements on the international maritime shipping network, based on a network equilibrium assignment methodology, under the given shipping demand between seaports. After the network structure of the model is modified and the model convergence and agreement with the current transhipment situation at worlds’ major hub ports are examined, the container flows transhipped at Colombo port are analysed. Subsequently, two kinds of simulation related to Colombo port are examined; improvement of transhipment cargo handling and construction of a new container hub in South India as a competitor. The latter simulation indicates that the transhipment containers in Colombo port would significantly decrease, if the new port can successfully attract all services operated by the largest shipping company, although the liner service network is provided and its change is not endogenised in the model.

This paper aims to evaluate port position in the Intra-Asian maritime container network based on centrality measures. From the results, main hub ports such as Singapore, Hong Kong, Busan, and Shanghai are identified as occupying pivotal positions in Intra-Asia in terms of centrality measures. Busan port is an important linkage for the pairs of other ports, especially for Japanese local ports. However, the closeness of Busan port is somehow lower, since its geographical advantage is relatively small in the Intra-Asia maritime network. Chinese and Taiwanese ports have more closeness due to their geographical centrality in the Intra-Asian network. Moreover, Surabaya port has high betweenness in Indonesia, which acts as an important bridge for Indonesian local ports in the Intra-Asia network.

This study evaluates the efficiency of Chinese and South Korean container terminals, including four automated and twenty traditional terminals, using data envelopment analysis. The study considers the following six input variables: water depth, quay length, storage area, number of quay cranes, number of gantry cranes, and number of terminal transfer vehicles. Container throughput is considered as the output variable. The most efficient terminals, located in the East China, are: SYCT (Shanghai), SIPG (Shanghai), SMCT (Shanghai), SSICT (Shanghai), and LNOCT (Lianyungang). In terms of relative performance, other terminals located along the Chinese coastline are ranked in the middle, and the terminals of South Korea perform relatively less efficiently. Although the superiority of automated container terminals is not as distinct as expected, there is a clear efficiency contribution from the crane input variable, and there is reason to believe that a time-series DEA analysis would emphasize this feature more prominently.

This paper aims to propose alternative modes of transport for Thailand-Myanmar’s cross-border trade at Ranong Province. The intermodal transport concept which connecting coastal shipping to road transport is applied to this study. The transport cost, which comprises of financial cost and environmental cost, is analyzed in aspect of macro view. The result shows that, when only the financial cost is analyzed, single mode of road transport would cost cheaper than intermodal transport while the latter would cost cheaper when environmental cost is included. To enhance sustainable transport and reveal its real cost, this paper suggests that Thai Government should promote this alternative by including environmental costs in the truck license fees. Furthermore, the related private sector such as coastal shipping lines, port operators, truck companies and exporters should cooperate closely on strategy planning.

Northern Sea Route (NSR) is focused on because it might bring a higher efficiency of logistics between Europe and Asia. However, until the route becomes a major transport route, there will be challenges. The purpose of this paper is to discuss both opportunities and challenges by focusing on different elements: technical feasibility, economic feasibility, and geopolitical/policy aspects. Regarding the technical feasibility, discussion starts with the monitoring of actual vessel movements. By analyzing transit time/reliability as well as navigability, current service levels and technical challenges are examined. Regarding the economic feasibility, we will mainly focus on the possible advantages of NSR for supply chain efficiency of shippers. Some conceptual ideas are proposed. Finally, the geopolitical and policy aspects are also critical. In this regard, recent policies including the Polar Silk Road are reviewed, and future prospects are examined.

The concept of industrial clusters has drawn considerable attention as a new perspective of regional and industrial policies in Japan. As for aerospace industry, Chubu region, including Aichi prefecture, was designated the International Strategic Comprehensive Special Zone in 2011. After providing an overview of the spatial concentration of aerospace industry at the municipal level in Japan, this paper aims to examine agglomeration economies with a special focus on aircraft parts industry in Aichi prefecture. The empirical results reveal strong evidence of urbanization economies or Jacobs type of externalities in contrast to maritime manufacturing sector. This suggests that knowledge spillovers and technological innovation could more easily occur in the industrially diversified environment. The paper concludes with the suggestion that agglomeration economies will play a more prominent role in the formation of aerospace industrial clusters.

This paper reviews the relevance of analyzing the data in a container terminal to provide useful information on how the terminal uses its resources. The daily operation in a container terminal faces many challenges, the container relocation problem or blocks relocation problem, is a classic example that occurs in day-to-day operation for facilities that use stacking systems. Data analysis is a potent tool to visualize and describe the actual behavior of any operation and finding its flaws. It aims to provide generic metadata related to handling containers in a terminal with the objective of understanding how terminal operation is done as well as its resource usage rates. It also describes an overview of a terminal’s stacking operation in a simulation model of stacking containers.

Big data analytics has triggered various advances in marine terminal research and information technology implementation. Specifically, for container terminals, big data technology has much to offer in understanding and consolidating information between port users and operators. One of the clear advantages for port operators is the opportunity to exploit the operational potential of cargo handling machinery. In 2015, we developed and introduced a method to effectively measure the performance of a hybrid straddle carrier (HSC) utilizing big data collection and analysis. Since 2017, this method has been used in the form of the Eco-Lamp prototype installed on HSCs at a medium-size container terminal in Japan. This study will analyze the effectiveness of that implementation, present the result achieved from the big data analytic point-of-view, and discuss the challenges and possible improvement of the system toward cost savings and efficient operation of port equipment.

Consignors, consignees, and freight forwarders need procedure status information on import and export containers, such as customs clearance, not only within a specific country but also across relevant countries in order to optimize supply chain management. In this paper, we review the current situation and literature on the sharing of procedure status information using IT systems. After clarifying issues in this regard, we present an IT system we have developed for sharing procedure status information in real time among Port Community Systems across countries. Finally, we discuss the issues and prospects in the development of the IT system. We conclude that, at present, it is beneficial to apply a decentralized system architecture in the sharing of procedure status information across countries without attaching any additional devices such as Radio Frequency Identification (RFID) tags.

This study aims to investigate the important factors affecting the driver`s injury severity of two-vehicle crashes between passenger cars (PCRs) and trucks (TRs) considering vehicle types. 5,579 crash data of PCRs with light motor trucks (LMTRs) and 5,287 crash data of PCRs with ordinary motor trucks (OMTRs) collected in Fukuoka Prefecture, Japan are used as the research sample. The drivers’ injury severity of PCRs with LMTRs and that of PCRs with OMTRs are modeled by two bivariate ordered probit models, respectively. Each ordered probit model in a bivariate ordered probit model measures the injury severity of one driver, and the covariance measures the correlation of injury severity. The major findings suggest: 1) that time of day, location, traffic condition, manner of collision and road type have different effects for two types of crashes; 2) that weather condition and age of drivers have similar effects for two types of crashes; 3) that the injury severity of two drivers involved in two types of vehicle crashes are negatively correlated, since two crash patterns i.e. no injury with minor injury and minor injury with no injury accounted for large ratios inside two types of crashes, which indicated that there is only one driver injured in most vehicle crashes of PCRs with TRs.