Can maritime big data be applied to shipping industry analysis? Focussing on commodities and vessel sizes of dry bulk ca
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Can maritime big data be applied to shipping industry analysis? Focussing on commodities and vessel sizes of dry bulk carriers Kei Kanamoto1 · Liwen Murong1 · Minato Nakashima1 · Ryuichi Shibasaki2 Accepted: 22 September 2020 © The Author(s) 2020
Abstract Enriched navigational information provided by an automatic identification system (AIS) could improve the estimation accuracy of trade patterns analysis by using different data sources. This paper estimates the global trade flow pattern of dry bulk cargo by commodity, namely iron ore, coal, grains, fertilisers, and iron and steel. We use AIS data and the information on commodities handled in ports, estimated by using a two-tiered Geohash geocoding. Estimation results are accurate at country level except for iron and steel. The results are used to quantify the impact of the previously identified variables on vessel size selection by regression analysis and a multinomial logit model. Finally, our model is used to forecast the future shipping demand by vessel type and commodity. Keywords AIS · Dry bulk · Port-based global cargo flow · Iron ore · Coal · Grains · Vessel size · AXS dry · Vessel movement
1 Introduction Resource (commodities) trade is critical to world economic growth because it supports the economic activities that consume energy. Given that international bulk shipping is highly volatile due to its dependence on energy supply and demand, it Winner of the MEL-Palgrave Macmillan-Springer Best Conference Paper Prize, IAME2020, Hong Kong Polytechnic University, Hong Kong. * Ryuichi Shibasaki [email protected]‑tokyo.ac.jp 1
Department of Systems Innovation, School of Engineering, The University of Tokyo, 7‑3‑1 Hongo, Bunkyo, Tokyo 113‑8656, Japan
2
Resilience Engineering Research Center, Department of Technology Management for Innovation, School of Engineering, The University of Tokyo, 7‑3‑1 Hongo, Bunkyo, Tokyo 113‑8656, Japan
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is crucial for carriers to comprehensively understand global trade flows. Although statistics on international trade are admittedly widely available, such as the UN Comtrade database, they are generally limited to country level. The developments in the automatic identification system (AIS) and satellite communication capabilities have allowed historical data to build up on ports of call, as well as sailing information on vessel movements. Although AIS data have been used in a variety of research applications, research on logistics to estimate global trade flows and transport patterns for each type of cargo remains scarce because the type of cargo and its handling at ports cannot be ascertained directly from the data. In this paper, we focus on dry bulk shipping, which accounts for 44% of seaborne trade volume. Dry bulk carriers carry three major bulk cargoes—iron ore, coal and grains—and minor bulks (e.g., wood, fertilisers, and iron and steel). There is a significant number of dry bulk carriers, calling at many ports. Moreover, a vessel often transports several commodities, therefore
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