Performance measure of dry bulk ports using shipping big data

Dry bulk port performance measure from a global macro perspective is important, as major dry bulk cargoes are closely linked to national industrial development. However, there is a lack of study systematically investigating dry bulk port performance measure using state-of-art technology, i.e., maritime big data. For a comprehensive comparison of worldwide dry bulk port performance, this study proposes a four-dimensional dry bulk port performance evaluation approach using automatic identification system (AIS) data. Dry bulk port performance is quantified in terms of connectivity, scale, efficiency and cargo flow. Using the top 15 iron ore ports as an example, the port performance of major iron ore ports is calculated and compared with AIS data in 2020. The constructed performance measure has been shown to effectively capture the key points for dry bulk ports to improve their performance, and provide insightful suggestions for both port operators and shipping companies.

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Publication Details

Journal
International Journal of Shipping and Transport Logistics
Published
2025-01-01
DOI
https://doi.org/10.1504/ijstl.2025.148489
Primary Topic
Maritime Ports and Logistics
Type
article
Field-Weighted Citation Impact
0.00
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article

Performance measure of dry bulk ports using shipping big data

Junhao Ren, Xiwen Bai, Wei Peng, Ji‐Qin Ni et al.
International Journal of Shipping and Transport Logistics
Maritime Ports and Logistics
article

Performance measure of dry bulk ports using shipping big data

Junhao Ren, Xiwen Bai, Wei Peng, Ji‐Qin Ni, Weihong Liu
article en

Abstract

Dry bulk port performance measure from a global macro perspective is important, as major dry bulk cargoes are closely linked to national industrial development. However, there is a lack of study systematically investigating dry bulk port performance measure using state-of-art technology, i.e., maritime big data. For a comprehensive comparison of worldwide dry bulk port performance, this study proposes a four-dimensional dry bulk port performance evaluation approach using automatic identification system (AIS) data. Dry bulk port performance is quantified in terms of connectivity, scale, efficiency and cargo flow. Using the top 15 iron ore ports as an example, the port performance of major iron ore ports is calculated and compared with AIS data in 2020. The constructed performance measure has been shown to effectively capture the key points for dry bulk ports to improve their performance, and provide insightful suggestions for both port operators and shipping companies.

International Journal of Shipping and Transport LogisticsVol. 21(2)
Ningbo No.6 Hospital (CN), Dalian Maritime University (CN), Tsinghua University (CN)
Openalex Percentile: Top 65%
Maritime Ports and Logistics
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