1st Edition
Shipping and Logistics Analytics using Big Data Automatic Identification System Data
Part 1. Introduction to Maritime Big Data
Chapter 1: General Introduction to Maritime Shipping using Maritime Trade Statistics
Ryuichi Shibasaki
Chapter 2: AIS Data and its Characteristics
Yujiro Wada, Daisuke Watanabe*1, Kunihiro Hamada
Chapter 3: VHF Data Exchange System: Maritime Big Data for the Next Generation
Nagateru Iwasawa, Takashi Ogai
Chapter 4: Combining AIS Data with Multiple Related Data Sources for Better Decision Making
Jue Wang, Dong Yang, Xiwen Bai
Part 2. Shipping Network Analysis using Maritime Big Data
Chapter 5: Vessel Navigation Network Development Using Trajectory Data
Lei Liu, Ryuichi Shibasaki
Chapter 6: Global Liner Shipping Network Connectivity Analysis
Liangqi Cheng, Xiwen Bai, Dong Yang
Chapter 7: Global Vessel Routing Analysis Focusing on the Suez Canal
Liluxin Chai, Trang Tran, Ryuichi Shibasaki
Chapter 8: Global Liner Shipping Network Resilience Analysis
Zhongjun Ma, Xiwen Bai, Dong Yang
Chapter 9: AIS Derived Fleet Productivity and the Case of the Russia-Ukraine War
Haiying Jia
Chapter 10: Maritime Disruption Analysis Focusing on Vessel Origins and Destinations: The Cases of the Red Sea and Panama Canal
Kenta Kowatari, Ryuichi Shibasaki, Yota Sasada, Takuma Matsuda
Chapter 11: Containerization and Semi-containerships in the age of Globalization: Diverse Regional Trends
Kenmei Tsubota, Hidekazu Itoh, Cesar Ducruet
Chapter 12: Optical Character Recognition of Lloyd's List Intelligence in 1880
Tomohiro Saito, Kenmei Tsubota, Ryuichi Shibasaki, Cesar Ducruet
Part 3. Vessel Operational Analysis using Maritime Big Data
Chapter 13: Vessel Operational Patterns and their Applications
Jiazhang Wu, Dong Yang, Xiwen Bai
Chapter 14: AIS-Based Vessel Trajectory and Destination Prediction
Xiwen Bai, Lerong Xu, Dong Yang
Chapter 15: Predicting Ship Position in Long Time Intervals Using End-to-end Deep Learning with AIS data
Ibadurrahman, Kunihiro Hamada, Yujiro Wada, Daisuke Watanabe *1
Chapter 16: Analysis of Vessel Schedule Recovery Policies in Liner Services Using AIS Data
Eisuke Watanabe, Sukanya Samanta, Kenta Kowatari, Ryuichi Shibasaki
Chapter 17: Geographical Analysis of Spot Contracts in Dry Bulk Shipping
Trang Tran, Ryuichi Shibasaki
Chapter 18: Extraction and International Comparison of Bunkering Services Using AIS Data
Eisuke Watanabe, Ryuichi Shibasaki, Wenru Zhang
Part 4. Green Transition and Maritime Big Data
Chapter 19: Fuel Consumption Estimation, Fleet Operations, and Emission Accounting
Haiying Jia
Chapter 20: Geographical Analysis of Vessel Emissions
Thuta Kyaw Win, Daisuke Watanabe *2
Chapter 21: Carbon Pricing, Emission Trading System, and AIS
Haiying Jia
Chapter 22: Emission Control Measures for Sustainable Arctic Shipping Activities
Chathumi Ayanthi Kavirathna, Ryuichi Shibasaki
Part 5. Logistics Analysis using Maritime Big Data
Chapter 23: Forecasting Shipping Freight Rates Using Big Data in Maritime Logistics
Yujiro Wada, Daisuke Watanabe *1, Kunihiro Hamada
Chapter 24: Short-term Forecast of Weekly Port Cargo Throughput with Machine Learning Models
Yujiro Wada, Ryuichi Shibasaki, Minato Nakashima, Yota Sasada
Chapter 25: Predicting Vessel Demand and Supply: Simulation-based Approach using AIS Data
Kazuhiro Aoyama, Takehiro Ishimatsu
Chapter 26: Cargo Handling Performance Analysis by Combining Satellite-derived Crane Operational Data and AIS
Hiroyuki Miyazaki, Yiran Sun, Ryuichi Shibasaki, John Ronan Y. Catillo, Val Kenneth Arado, Christian Mark Parame
Biography
Ryuichi Shibasaki is an Associate Professor at the Department of Systems Innovation, School of Engineering, The University of Tokyo. After getting PhD, he worked as a researcher at the National Institute for Land and Infrastructure Management, Ministry of Land, Infrastructure, Transport and Tourism, Japan for 15 years, and returned to The University of Tokyo in 2017. His research focus is primarily on global intermodal freight flow modelling, port logistics, and maritime big data analysis. Dr. Shibasaki’s research has received awards including three for “Best Application in Practices” from the Eastern Asia Society of Transport Studies (EASTS) and two from the International Association of Maritime Economists (IAME). He currently serves as an associate editor of Maritime Policy & Management, International Journal of Shipping and Transport Logistics, and Asian Transport Studies. Also, he is one of the representative organizers of the International Conference on Transportation and Logistics (TLOG Network).
Dong Yang is an Associate Professor at The Hong Kong Polytechnic University, where he also holds positions as the associate head of the Department of Logistics and Maritime Studies, director of Doctor of International Shipping and Port program joint with Zhejiang University (D.ISP) and International Shipping and Transport Logistics Master Program (ISTL), director of PolyU Maritime Data and Sustainable Development Centre, deputy director of Research Centre for Environmental, Social, and Governance Advancement. Dr. Yang serves as an associate editor for the International Journal of Shipping and Transport Logistics (IJSTL) and Maritime Policy & Management (MPM) and an editorial board member of the Journal of Transport Geography and Transportation Research Part E and Maritime Economics & Logistics. Prof. YANG obtained his Ph.D. in maritime logistics science from Kobe University, Japan, in 2008. After that, he has successively served as an assistant professor at the Southern University of Denmark, a research fellow at the Centre for Maritime Studies, National University of Singapore, and a senior research fellow at China Waterborne Transport Research Institute.
Xiwen Bai is currently an Associate Professor with the Department of Industrial Engineering, Tsinghua University. She received the B.S. and Ph.D. degree from Nanyang Technological University. Her main research interests include maritime economics and digital shipping. Her research has been published in leading international journals including Transportation Science and Transportation Research Part series. She also serves as associate editor for Maritime Policy & Management, a flagship journal in maritime transportation management.
Haiying Jia is Professor of Quantitative Business Economics at the Norwegian School of Economics (NHH). She earned her PhD in Finance from Bayes Business School, City University of London, the United Kingdom, and previously worked in London as a Quantitative and Investment Analyst in the finance industry. She also holds an Honorary Professorship at Bayes Business School. An internationally recognized scholar in shipping economics and maritime data analytics, Professor Jia has spent more than a decade pioneering the use of maritime Automatic Identification System (AIS) big data to study shipping markets, global trade, and financial dynamics in maritime industries. Her research bridges economics, finance, and maritime analytics, offering perspectives on how large-scale shipping data can inform research on international trade and global supply chains. She has been a visiting scholar at leading institutions worldwide, including the Massachusetts Institute of Technology (MIT), the University of Tokyo, and Nanyang Technological University. Drawing on her combined experience in academia, the finance industry, and entrepreneurship, Professor Jia’s work advances innovative approaches to understanding maritime trade and the evolving role of AIS data in global economic systems.
