Asian Journal of Shipping and Logistics最新文献

Foreign Direct Investment (FDI) plays an important part in the economic growth of developing Asia and logistics capability is a crucial factor in FDI location choice. Till today, research investigating Logistics Performance (LP) and FDI in Asia are still lacking and rather inconclusive and not standardised. Using a total of 31 Asian countries covering 2007 through 2017, the study critically investigates the impact of LP on FDI using static panel regression method. The results demonstrate that while LP significantly impact FDI, there is a threshold effect of institutional quality in the LP-FDI relationship. Specifically, this paper found that the impact of LP on FDI varies across the perceived level of institutional quality i.e., the effect is positive only before certain threshold level of institutional quality, after which the effect of LP on FDI is reversed. This finding suggests that the LP-FDI nexus is contingent on the perceived level of institutional quality, thus supporting the idea that innovations (i.e., creativity and flexibility embedded within a sound institutional framework) is potent in delivering long-run LP-FDI development in Asia.

Decision-making for shelter location-allocation influences the success of disaster response and affects the security of victims. This paper proposes a multi-objective optimization model for determining shelter location-allocation in response to humanitarian relief logistics. Three objective functions are formulated to improve both efficiency and effectiveness. The first objective is to minimize total costs, including fixed costs for opening the shelters, transportation costs, and service costs. The second objective is to minimize the total time for evacuating victims from all affected areas to allocated shelters. The third objective is to minimize the number of shelters required to provide thorough service to victims. The Epsilon Constraint method (EC) and Goal Programming (GP) are employed for solving the proposed model. The applicability of the proposed model is validated through a case study of flooding in Surat Thani, Thailand. The Pareto efficiency obtained from solving the proposed model is compared with current shelter location-allocation plans determined by the government sector. The comparisons reveal that the results obtained from solving the proposed model outperform current shelter location-allocation plans. Furthermore, the results of this study could provide an advantage to decision-makers considering appropriate strategies for disaster response.

Designating the ideal shipping route can spare expenses, enlarge profits and improve the competitiveness of shipping companies. Liner shipping route choice is mainly contingent on fuel cost, which always contributes the major proportion of the ship's operating cost. Although many studies on this topic have been carried out, none are based on the fuel consumption forecast model designed by the advanced machine learning method. This paper provides a platform idea for selecting the optimal operating route for container ships to minimize fuel cost by using an asymmetric traveling salesman problem (ATSP) algorithm solution, in which the fuel consumption model for the route is estimated based on the deep-machine learning method. Five input variables are given in the model including average velocity, sailing time, ship's capacity, wind speed, and wind direction. The mean absolute percentage error (MAPE) of the model is 5.89%, indicating that the predictive result obtains a very high accuracy, close to 95%. The optimal model is thus applied in combination with ATSP to address the optimal solution for a certain route.

Despite the number of studies on the efficiency of container ports, most studies are of developed nations, and very few are of developing nations, such as India. Indian container ports are very critical due to their location advantage and their ability to handle transhipment traffic. There is a need to understand their performance at the micro-level, specifically the terminal level rather than that of the whole port. This paper focuses on the analysis of the technical efficiency of 26 container terminals in India using a data envelopment analysis approach for the years 2015–2018 and interprets it with respect to location advantage, administrative control and private control of terminal operations. The research explores the Malmquist index which measures productivity changes over a period of time and deconstructs them into two components, namely efficiency change, referred to as catch-up, and frontier shift. This study enabled the ranking of these terminals in terms of their performances. The relative efficiency of container terminals on the west coast of India is found to be better than that of the east coast of India, and the efficiency of container terminals operating under major ports is on a declining path when compared with that of minor ports. The private participation has also not seen similar productivity changes across all container terminals. Among the seven high performing container terminals identified through the analysis provided, the terminal at Tuticorin emerged as the most consistent one in terms of relative efficiency and growth in total factor productivity. The dominant factor influencing the efficiency of a terminal is found to be the size of the terminal, offering the advantages of economies of scale.

We investigate and quantify the relationship between agricultural commodities and ocean-going freight rates, using a weekly dataset from 2010 to 2019 and a Vector Error Correction Methodology. The results are firstly supportive of the view that vessel classes are highly interconnected, and secondly confirm that commodity prices can have a strong impact on freight rates across most vessel classes. For commodities in which no impact is registered on freight rates, the possibility of substitution effects exists. Furthermore, the results indicate that the markets in which these products trade can be a significant determinant of future freight rate movements. These findings can be particularly useful for agricultural businesses that are concerned with the transportation cost of their products and the ways that the latter can be mitigated.

This paper explores the structure of the seaport life cycle (SLC) of Malaysian container seaports to restructure the seaport development plan. Quadratic regression analysis is proposed to stratify the life cycle stages of seaports through the quantification of throughput volume, and forecast future growth patterns of seaports. The findings show that Port Klang, Penang Port, PTP and Kuantan Port are experiencing the growth stage in their seaport life cycles, while Johor Port is standing at the decline stage of the seaport life cycle. Penang Port and Port Klang are expected to continue growing until 2050. Meanwhile, PTP, Johor Port and Kuantan Port have entered the maturity stage in 2018 and are expected to move into the declining stage by 2050. This paper provides significant evidence about the need to establish a link between seaports and dry ports, and develop a symbiotic strategy to prolong the life cycle of seaports. Academically, this paper provides significant literature on Malaysian seaport cycles, which may be utilised for seaport development plans to cater to the demands of the domestic and global market.

The shortage of seafarers continues in the global shipping market. In particular, the retention of skilled officers has not been maintained. One of the reasons why the number of officers working on merchant ships is because of the working conditions onboard the ship. For instance, there are work-life balance, contractual employment, high workload and stress levels, insufficient shore leave, and career progression, and so on. Therefore, some public system is required for the seafarers to prepare for a stable life after they leave a ship while working on the ship to relieve anxiety. Among the many ways, the seafarer's retirement pension system is a practical and effective way to ensure a stable life for seafarers. The retirement pension system can be applied differently depending on the characteristics of the employees and companies that are subscribers, and their effects can also be different. So, in this study, we are intended to analyze what type of retirement pension seafarers prefer in Korea. Retirement pension is generally classified into defined benefit (DB), defined contribution (DC) and individual retirement pension (IRP). To survey the seafarers’ preference on retirement pension by type, six hypotheses were established using company variables and seafarer variables. Company variables include the type of business and the number of seafarers employed by shipping company while seafarer variables include the service term, age, type of duty (ship's officer, sailor), and annual wage of the seafarer. To verify the established hypotheses, the survey of the seafarers who are currently employed by the shipping company was carried out. A cross-tabulation analysis among the statistical analysis approaches was performed and the chi-squared statistic was calculated to validate the hypotheses. Consequently, the preference varied depending on the service term and age of the seafarers. That is, the shorter the service term and the younger, individual retirement pension which allows personal asset management was preferred while those who have longer service term and older-age tended to prefer defined benefit. The outcome of this study is expected to be useful for the shipping company to design the retirement pension system for seafarers. Ultimately, the introduction of a seafarer retirement pension system will contribute to the influx of skilled crews, the competitiveness of the shipping company, and reduced marine accidents.