Kenta Kowatari

dblp:397/8583 · DBLP profile ↗
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2ranked-venue papers in the field
1as first author
2since 2021 · last 2025
—ORCID · none

Domains — venue-derived; a paper can count in several

Big Data, Cloud & Distributed Data Systems · 2 (1 first)
YearPublicationVenuePosition
2025 Schedule Recovery Strategies in Container Liner Shipping Networks Using Multi-Agent Simulations
Kenta Kowatari, Ryuichi Shibasaki
IEEE Big Data1
2024 On Vessel Schedule Delay and Its Recoveries in Liner Services Using AIS Data
abstract
Maintaining the reliability of maritime transport is important as it plays an essential role in the world’s logistics. Shipping companies must also ensure the quality of liner service from the viewpoint of punctuality, as failure to take appropriate action against transport delays can lead to significant financial losses. This study quantitatively analyzes the behavior of containerships in response to global transport delays in 2021 caused by the COVID-19 pandemic using Automatic Identification System (AIS) data and port call history data. This study first comprehensively reveals the delay of containerships in 2021 by highlighting the increased variability in vessel arrival times, decreased handling capacities in specific ports, and increased navigation and anchorage times. Subsequently, this study clarifies how vessels recovered their schedule by increasing ship speeds or skipping some ports. We found vessel speeds susceptible depending on their delay in some specific voyages, such as long-distance cross-regional navigation.
Eisuke Watanabe, Sukanya Samanta, Kenta Kowatari, Ryuichi Shibasaki
IEEE Big Data3