2020.6.24（Wed）Awards and Commendations
【Awards and Commendations】Kei Kanamoto (graduated in March 2020) and other authors received Maritime Economics & Logistics Best Conference Paper Award at Annual Conference of International Association of Maritime Economists.
1. Kei Kanamoto(a), Liwen Murong(b), Minato Nakashima(b), and Ryuichi Shibasaki(c)
2. (a) Department of Systems Innovation (Graduated in March 2020), Graduate school of Engineering
(b) M2 student, same as above
(c) Associate Professor, Resilience Engineering Research Center, Department of Techonology Management for Innovation (TMI)
3. Name of award and short explanation about the award
International Association of Maritime Economists (IAME) is an association that not only researchers, but practitioners, consultants, and governmental officers on the maritime shipping and logistics field join. This year’s annual conference was held online on June 10 to 13, hosted by Hong Kong Polytechnic University, having more than 220 presentations. The paper “Can Maritime Big Data be Applied to Shipping Industry Analysis? - Focusing on Commodities and Vessel Size of Dry Bulk Carriers” submitted from Shibasaki Lab was awarded “Maritime Economics & Logistics Best Conference Paper Award” as one of the four best papers of the conference.
4. About awarded research
The paper is based on the Master thesis that Mr. Kanamoto, the first author of this paper, submitted at the end of last fiscal year. First, the global cargo flows shipped by dry bulk carriers were estimated on a port-basis by commodity including iron ore, coal, grain, fertilizer, and iron and steel. Subsequently, the vessel type selection model was developed by commodity, considering the difference in the effect of each variable, such as trade volume, shipping distance, draught limitation of export and import ports, and size limitation to transit canals, then applied to forecast the future shipping demand by vessel type.
5. Your impression & future plan
The Automatic Identification System (AIS) data, which records the movements of all kinds of vessels over a certain size, is a big data in the maritime shipping field; however, the cargo information are not included. This paper enabled to estimate the cargo flow by combining other available information. We consider that the novelty and innovativeness of our approach was proved by this award, which will encourage the advancement of our research further. (Ryuichi Shibasaki)
The Japan Maritime Daily (24th/June/2020)