Asian Journal of Shipping and Logistics最新文献

The growth of last-mile delivery in developing countries is featuring the important contribution of crowdshippers. Therefore, exploring the factors affecting the intentions to stay in jobs of the crowdshippers is of great significance to maintain and sustainably develop the last-mile delivery service. Based on the Social Exchange Theory, we hypothesize that benefits (economic benefits, professional reputation, and job autonomy) and costs (risks and stress at work) have an effect on crowdshippers’ intentions to continue participating in last-mile delivery service in Vietnam. We also look for differences in motivations to stay in job between full-time and part-time workers. Survey data from 428 crowdshippers were analyzed using SmartPLS. The research findings indicate that economic benefits and work autonomy (benefits) have positive influences on intention to continue participating in crowd logistics, while risks and job stress (cost) have negative effects on the intention of crowsdhippers to continue their work. In addition, research findings also uncover that differences in motivation (perception of benefits and costs) to stay in job between full-time and part-time workers also affect their intentions. Although reputation did not show a significant impact on the crowdshippers’ intentions to continue participating in crowd logistics, it was discovered that reputation has a positive effect on full-time crowdshippers’ intentions to continue working. Based on the findings of this study, we recommend that businesses increase benefits and reduce costs in job to sustain and increase the continued participation in last-mile delivery.

As smart and environmentally friendly technologies and equipment are introduced in the sea port industry, electric power consumption is expected to rapidly increase. However, there is a paucity of research on the creation of electric power management plans, specifically in relation to electric power consumption forecasting, in ports. In order to address this gap, this study forecasts future electric power consumption in Busan New Port (South Korea's largest container port) and, comparing this with the current standard electric power supply capacity, investigated the feasibility of maintaining a stable electric power supply in the future. We applied a Long Short-Term Memory (LSTM) model trained using electric power consumption and throughput data of the last 10 years to forecast the future electric power consumption of Busan New Port. According to the results, electric power consumption is expected to increase at an annual average of 4.9 % until 2040, exceeding the predicted annual 4.7 % increase in throughput during the same period. Given these results, the current standard electric power supply capacity is forecast to reach only 35 % of demand in 2040, indicating that additional electrical power supply facilities will be needed for stable port operation in the future.

This study aimed to analyze the research trends of inland waterways in the field of logistics by compiling previous studies that contain keywords related to inland waterways. To investigate the research trend, this study used a keyword network among the SNA methodology and deduced results using the concepts of centrality, including degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. According to the results of the comprehensive analysis by each region based on the eigenvector centrality outcome, Europe had a core keyword of modal shift, which refers to the conversion to eco-friendly vehicles due to the exhaust problem of land carriage, as well as the continuously implemented government policy. The results of China showed that the country’s task to solve was on studies aimed at reducing traffic jams in inland waterways using AIS data. In the case of the US, the problems of ship delay remain unsolved owing to old locking facilities and equipment. This study provided academic implications that clarify the state-of-the-art in this research topic in three regions that have advanced inland waterways.

The rapid development of the Internet of Things (IoT) devices led to new era in the maritime and road transportation industry and research. This article studies the critical determinants of Drone delivery services (personal innovativeness, outcome expectancy, positive anticipated emotions, and perceived risk) on customer willingness to use Drone in an emerging economy. The article employs correlation analysis and structural equation modeling (SEM) to analyze the data of 602 valid observations collected in the structured questionnaire survey in Vietnam. Empirical results indicate that outcome expectancy and personal innovativeness positively impact customer attitude and anticipated emotion, while outcome expectancy has the strongest influence. These findings also show that outcome expectancy and personal innovativeness have an effect on customer willingness to use Drone through their positive attitude and positive anticipated emotions. Interestingly, the perceived risk of Drone is considered a moderator in reducing the relationship between customer attitude and willingness to use Drone while it has an insignificant impact on customer emotion and willingness to use.

Currently, inland water transport is the main mode of transport in the Republic of Sakha (Yakutia). The Lena remains the main river connecting Yakutia with the federal transport infrastructure. However, the state of the Republic’s transport infrastructure does not meet the needs of its economy The infrastructure limits the effective realization of the industrial and resource potential and use of the geographical position of the Republic of Sakha. Therefore, to provide an insightful analysis of the factors affecting the logistics of the Lena River, we conducted a detailed analysis of the current problems of the inland waters of the Republic. This article analyzes the logistics of the Lena River and presents an assessment of the problems hindering the process of modernizing the inland water transport of the Republic of Sakha. Analyzing the factors for revitalizing the Lena River logistics through the Interpretative Structural Modeling method revealed the region’s main water transport logistics problems. Through the literature review, 12 key factors affecting the logistics of the Lena River were identified, and interrelationships among them were represented. The results illustrate that inland water transport of the Republic requires the development of transport infrastructure and financial support from the state to implement republican targeted programs. Therefore, this study is important in both academic and practical aspects.

Forecasting container throughput is critical for improved port planning, operations, and investment strategies. Reliability of forecasting methods need to be ensured before utilizing their outcomes in decision making. This study compares forecasting performances of various time series methods, namely autoregressive integrated moving average (ARIMA), seasonal ARIMA (SARIMA), Holt-Winter's Exponential Smoothing (HWES), and the Prophet model. Since forecast combinations can improve performance, simple and weighted combinations of ARIMA, SARIMA and HWES have been explored, too. Monthly container throughput data of port of Shanghai, Busan, and Nagoya are used. The Prophet model outperforms others in the in-sample forecasting, while combined models outperform others in the out-sample forecasting. Due to the observed differences between the in-sample and out-sample forecast accuracy measures, this study proposes a forecast performance metric consistency check approach for informed real-world applications of forecasting models in port management decision-making.

The shipping industry continues to have strong growth prospects due to increased efficiency and economic liberalization. Through seaborne trade, port infrastructure and logistics impact economic growth in developing countries. This makes studying the factors affecting seaborne trade for such countries particularly important. The current paper aims at analyzing the impact of logistics, economic, and demographic variables on seaborne commodity trade between Qatar, Oman, Turkey, Pakistan, and Iran. Employing a gravity model, results show that a 1% improvement in Logistics Performance Index (LPI) consignments in the importing country can result in a 0.8% increase in total trade flows. Based on results, a 1% increase in the tariff rate reduces the value of trade by 0.4%. Furthermore, a 0.5% increase in trade is caused by the increase in population of the destination country. A sensitivity analysis also shows that logistics variables are more significant than economic and demographic variables. It can be concluded that trade policymakers in developing countries can get better results by improving logistics performance and investing on logistics infrastructure leads to more trade.

This paper studies the behaviour of shipping investors following an unexpected shock in the freight rates, while accounting for costs (fuel), and the macro environment (stock prices and trade). The estimates firstly confirm the existence of a long-term relationship between the macroeconomic environment and freight rates, as well as between that and newbuilding orders. Most importantly, we find that when the source of the shock is less clear but still causes an increase in freight rates, shipping investors respond with a delay, which could last almost a year. The thinking behind this “inaction period” is rational, given that the only way to observe whether a shock is permanent or transitory is to wait it out. The above findings have important policy implications not only for shipping investors but also for countries that rely heavily on their ship-building industries.

Ports form important links in the overall trade chain and act as driving forces for marine economic development. However, the operation of ports also has certain difficulties and challenges that port operators need to overcome. As such, this research aims to measure the performance efficiency of 22 ports listed in the stock market in Vietnam – a developing country with notable progress and role in global seaborne transport. The hybrid method of Delphi technique with KAMET principle and input and output – oriented DEA method was applied to solve the problem of efficiency assessment. The Delphi technique with KAMET principle was used to determine the efficiency evaluation criteria whilst the input and output – oriented DEA was employed to measure the efficiency. The findings show that capital, operation expenses, labour, port area, quay length, depth, revenue, and cargo throughputs are considered as input and output variables in the port efficiency evaluation. Additionally, it is also concluded in the research that scale and management skills are the dominant source of efficiency and Vietnamese ports show rather high management skills. Moreover, comprehensive and multi-variable assessment of port system may bring lots of benefits not only to the decision-making units but also the maritime authorities within constraint funds.

The freight rate is a representative variable in the shipping market and is characterized by a cyclical relationship. Even though downturns in the shipping market, such as the shipping industry recession in the 1980s, the global financial crisis in 2008 and COVID-19 crisis in 2020, recur, few studies have analyzed the dynamic relationship between supply and demand in terms of its effect on freight rates. Thus, this study classifies the factors affecting fluctuations in dry cargo freight rates into demand, supply, and freight rate specific demand factors, which play the most important role in managing risk in the shipping market. Based on the recursive structural vector autoregressive (recursive SVAR) model, we analyze the historical contributions of the effects of each factor across different time periods. Two main findings are summarized as follows: first, we identify the dynamic relationship between factors affecting BDI in the shipping market, and reveal that the magnitude and direction of factors are different. Second, we verify that in an extreme situation in which freight rates exceed the normal range, the market is overheated, and freight rates are therefore determined by the freight rate specific demand of market participants rather than by the actual supply and demand.