Holistic Tactical-Level Planning in Liner Shipping with Heterogeneous Vessel Fleet
Junayed Pasha, Florida A&M University-Florida State UniversityShow Abstract
Maxim Dulebenets (firstname.lastname@example.org), Florida A&M University-Florida State University
Oluwatosin Theophilus, Florida A&M University-Florida State University
Yui-yip Lau, Hong Kong Polytechnic University
The magnitude of maritime transportation has been increasing over time. Container demand has been growing as well, although the COVID-19 pandemic may slow down this trend for some time. Liner shipping companies have been using different strategies to effectively serve the existing customers. One of the common strategies is the deployment of large vessels. The current practice in the liner shipping industry is to deploy a combination of vessels of different types with different cargo carrying capacities (i.e., heterogeneous fleet), especially at the routes with a significant demand. However, heterogeneous fleets of vessels have been investigated by very few studies, which addressed the tactical-level decisions in liner shipping (i.e., determination of service frequency, fleet deployment, optimization of sailing speed, and design of vessel schedules). Moreover, little research efforts have been carried out to provide all the tactical-level decisions in liner shipping using a single solution methodology. Therefore, this study proposes an integrated mixed-integer nonlinear programming model, which addresses all the tactical-level decisions in liner shipping and allows the deployment of a heterogeneous vessel fleet at each port rotation. A heuristic algorithm is developed to solve the proposed model and effectively tackle large-size problem instances. The numerical experiments, carried out for a number of real-world liner shipping routes, demonstrate the effectiveness of the proposed methodology. Some managerial insights, obtained from the proposed methodology, are also provided.
Impact of the COVID-19 lockdown on the maritime transportation
Hong-Mei Zhao (email@example.com), Shanghai Maritime UniversityShow Abstract
Hong-Di He, Shanghai Jiao Tong University
Yu-Hang Jiang, Shanghai Jiao Tong University
Zhong-Ren Peng, University of Florida
The rapid spread of the Corona Virus Disease 2019 (COVID-19) has had a major impact on maritime transportation. China and the global successively entered lockdown in the early first and second quarter in 2020 to contain the spread of the pandemic. In this paper, the Baltic Dry Index, the China Coastal (Bulk) Freight Index (comprehensive index), and the container throughput are analyzed to examine the effect of lockdown on dry bulk and container transportation. The results reflect that both the domestic and international dry bulk transportations are significantly affected by lockdown measures in the second month, especially for an extremely sharp “shock” to the international market. Container transportation also experiences a degree of negative impacts from the lockdown measures. Measures play a prominent role in the Port of Los Angeles and Shanghai Port. In addition, in contrast to the 2008 global financial crisis, it is found that the impact of the pandemic on the dry bulk transportation is significantly less than that of the global financial crisis, but has a greater short-term impact on the container transportation.
China’s International Liner Shipping Network Evolution and Vulnerability Based on Automatic Identification System (AIS) Data
LIANJIE JIN, Ministry of Transport of the People’s Republic of ChinaShow Abstract
ZILIN CHEN, Dalian Maritime University
XIANFENG WANG, Dalian Maritime University
Haiyuan Yao, Ministry of Transport of the People’s Republic of China
CHANGJIAN LIU, Dalian Maritime University
BIN YU, Dalian Maritime University
Container shipping network is an important basis for global manufacturing and supply chain operation. China’s international liner shipping network has become one of the most essential sub-networks of the global container shipping network. Based on ship Automatic Identification System (AIS) data, this paper calculated the leading indicators of complex networks of China’s international liner shipping network, the Belt and Road network, the China-US network, and the China-Africa network. Analyzed the network characteristics, port importance, and network evolution and vulnerability. The study found that, from 2016 to 2019, the scope of China’s international liner shipping network was expanded. The number of nodes increased from 468 to 622, and the efficiency of the network has increased by 7.8%. In the meantime, the importance of ports in the network has changed, as Busan replaced Singapore as the highest connectivity node of China's container shipping network. Moreover, the paralysis of Busan, Singapore, Hong Kong, Antwerp, and Port Said has a significant impact on China's foreign trade route network transportation. This study helps us to assess the vulnerability of shipping networks under the impact of COVID-19 and provides useful Suggestions for maintaining global supply chain security.
Comparative Carbon Footprint Assessment of Cross-border E-commerce Shipping Options
Lynette Cheah (firstname.lastname@example.org), Singapore University of Technology and DesignShow Abstract
Qiuhong Huang, Singapore University of Technology and Design
In the bid to stay competitive, online shopping platforms often offer a variety of shipping options to meet the preferences of consumers. While faster delivery might be desirable for consumers, this may be detrimental to the environment and may not even be necessary in the first place. Limited studies have been conducted on the comparative environmental impact regarding different shipping options offered by e-commerce platforms. To fill this gap, this study aims to first conduct a comparative carbon footprint assessment of the shipping options available in Taobao, a highly popular Chinese e-commerce website. We evaluate the case of cross-border e-commerce, where goods are ordered from China to Singapore as the shipment destination. Thereafter, a shipping choice preference survey is conducted to evaluate the impact of carbon labelling on consumers’ shipping preferences. From the perspective of the consumer, when offered a variety of shipping options to choose from, there is always a trade-off between the cost and the speed of delivery. It could be beneficial if they are also provided with additional information on the carbon impact of different options to aid with their decision-making. The shipping options from Taobao are referenced to determine the cost, speed, and carbon emission values for the scenarios presented in the survey. Out of 188 survey respondents, slightly more than half (55%) were found to be willing to compromise the speed of delivery for a less carbon-intensive alternative. Given this finding, the study advocates for carbon labelling to be introduced for e-commerce shipping options.
Spatial Analysis of the 2018 Logistics Performance Index Using Multivariate Kernel Function to Improve Geographically Weighted Regression Models
Ivan (Runhua) Xiao, University of California, DavisShow Abstract
Miguel Jaller, University of California, Davis
David Phong, California Department of Food and Agriculture
Haihao Zhu, University of California, Davis
This paper analyses the 2018 Logistics Performance Index (LPI) from the World Bank to determine the spatial effects of countries’ logistics performance. Although the standardized ordinary least square (OLS) models show good results, the spatial lags and Moran’s I of LPI suggest the OLS assumptions are violated. Consequently, the authors implement an Improved Geographically Weighted Regression (IGWR) model using Multivariate Kernel Functions (MKF) to estimate the weight matrix. Through the analysis of the Moran scatter plot, the authors identified the countries that have different logistics performance development trends in the four quadrants representing the relationship between the spatial lags and the LPI. Using trade activity (i.e., import/export) in the MKF, the authors compared different MKF types and bandwidths to ensure the model’s predictability and accuracy and found that the adaptive Gaussian MKF is suitable. Finally, the IGWR model indicates that GNI per capita, ease of doing business score, GDP, quality of port infrastructure, rail lines and burden of customs procedure have a positive influence over LPI overall score, while commercial vehicles registrations, import of transporter or bridge cranes and time to import exhibit a negative effect. Also, the IGWR model shows a continental clustered spatial pattern of the coefficients where some countries’ LPI scores are more sensitive to equivalent changes, resulting in different contributing factors of logistics performance for various countries. This spatial heterogeneity is related to the specific factors that promote the development of their logistics performance.
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