Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data
The dry bulk shipping network is an important carrier of global bulk commodity flow. To better understand the structural characteristics and future development trends of the global dry bulk shipping network (GDBSN), this study proposes a framework for characteristics analysis and link prediction bas...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/1/147 |
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| author | Haijiang Li Xin Zhang Peng Jia Qianqi Ma |
| author_facet | Haijiang Li Xin Zhang Peng Jia Qianqi Ma |
| author_sort | Haijiang Li |
| collection | DOAJ |
| description | The dry bulk shipping network is an important carrier of global bulk commodity flow. To better understand the structural characteristics and future development trends of the global dry bulk shipping network (GDBSN), this study proposes a framework for characteristics analysis and link prediction based on complex network theory. The study integrates large-scale heterogeneous data, including automatic identification system data and port geographic information, to construct the GDBSN. The findings reveal that the network exhibits small-world properties, with the Port of Singapore identified as the most influential node. Link prediction results indicate that many potential new shipping routes exist within regions or between neighboring countries, exhibiting clear regional clustering characteristics. The added links mainly influence the local structure, with minimal impact on the overall network topology. This study provides valuable insights for shipping companies in route planning and for port authorities in developing strategic plans. |
| format | Article |
| id | doaj-art-7c36c1e6bef74e14a553573cbc30e2e6 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-7c36c1e6bef74e14a553573cbc30e2e62025-01-24T13:37:01ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-01-0113114710.3390/jmse13010147Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big DataHaijiang Li0Xin Zhang1Peng Jia2Qianqi Ma3School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaSchool of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaSchool of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaSchool of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, ChinaThe dry bulk shipping network is an important carrier of global bulk commodity flow. To better understand the structural characteristics and future development trends of the global dry bulk shipping network (GDBSN), this study proposes a framework for characteristics analysis and link prediction based on complex network theory. The study integrates large-scale heterogeneous data, including automatic identification system data and port geographic information, to construct the GDBSN. The findings reveal that the network exhibits small-world properties, with the Port of Singapore identified as the most influential node. Link prediction results indicate that many potential new shipping routes exist within regions or between neighboring countries, exhibiting clear regional clustering characteristics. The added links mainly influence the local structure, with minimal impact on the overall network topology. This study provides valuable insights for shipping companies in route planning and for port authorities in developing strategic plans.https://www.mdpi.com/2077-1312/13/1/147shipping networkdry bulk shippingautomatic identification systemcomplex networklink prediction |
| spellingShingle | Haijiang Li Xin Zhang Peng Jia Qianqi Ma Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data Journal of Marine Science and Engineering shipping network dry bulk shipping automatic identification system complex network link prediction |
| title | Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data |
| title_full | Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data |
| title_fullStr | Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data |
| title_full_unstemmed | Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data |
| title_short | Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data |
| title_sort | research on the pattern and evolution characteristics of global dry bulk shipping network driven by big data |
| topic | shipping network dry bulk shipping automatic identification system complex network link prediction |
| url | https://www.mdpi.com/2077-1312/13/1/147 |
| work_keys_str_mv | AT haijiangli researchonthepatternandevolutioncharacteristicsofglobaldrybulkshippingnetworkdrivenbybigdata AT xinzhang researchonthepatternandevolutioncharacteristicsofglobaldrybulkshippingnetworkdrivenbybigdata AT pengjia researchonthepatternandevolutioncharacteristicsofglobaldrybulkshippingnetworkdrivenbybigdata AT qianqima researchonthepatternandevolutioncharacteristicsofglobaldrybulkshippingnetworkdrivenbybigdata |