Spatial-temporal analysis of the international trade network
With the support of spatial-temporal data analysis technologies and network science, the International Trade Network (ITN) research has made significant progress, demonstrating broad application prospects in mining market evolution and predicting trade dynamics. Based on all ITN research cases from...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-01-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2024.2449458 |
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| _version_ | 1841525320979578880 |
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| author | Donghai Liu Ziwen Yang Kun Qin Kai Li |
| author_facet | Donghai Liu Ziwen Yang Kun Qin Kai Li |
| author_sort | Donghai Liu |
| collection | DOAJ |
| description | With the support of spatial-temporal data analysis technologies and network science, the International Trade Network (ITN) research has made significant progress, demonstrating broad application prospects in mining market evolution and predicting trade dynamics. Based on all ITN research cases from 2003 to 2023, this paper presents a research framework for ITN analysis, reviewing its advancements in data collection, visualization, topology analysis, structure prediction, and correlation analysis, where the spatial-temporal data analysis technologies have provided crucial methodologies and insights. A multilevel scenario construction theory for complex networks is proposed, highlighting the great significance of spatial regression models and system dynamics models in identifying global mechanisms; the unique value of temporal network analysis under the support of time-series information is discussed. Given the existing limitations, the development of more granular and reliable datasets utilizing big data technologies, as well as the construction of richer spatial-temporal scenarios, are considered as future research agendas. |
| format | Article |
| id | doaj-art-bb4489358e1e4bdab0aad3c4808e1ff0 |
| institution | Kabale University |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-bb4489358e1e4bdab0aad3c4808e1ff02025-01-17T14:57:09ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-01-0112910.1080/10095020.2024.2449458Spatial-temporal analysis of the international trade networkDonghai Liu0Ziwen Yang1Kun Qin2Kai Li3School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaEconomics and Management School, Wuhan University, Wuhan, ChinaWith the support of spatial-temporal data analysis technologies and network science, the International Trade Network (ITN) research has made significant progress, demonstrating broad application prospects in mining market evolution and predicting trade dynamics. Based on all ITN research cases from 2003 to 2023, this paper presents a research framework for ITN analysis, reviewing its advancements in data collection, visualization, topology analysis, structure prediction, and correlation analysis, where the spatial-temporal data analysis technologies have provided crucial methodologies and insights. A multilevel scenario construction theory for complex networks is proposed, highlighting the great significance of spatial regression models and system dynamics models in identifying global mechanisms; the unique value of temporal network analysis under the support of time-series information is discussed. Given the existing limitations, the development of more granular and reliable datasets utilizing big data technologies, as well as the construction of richer spatial-temporal scenarios, are considered as future research agendas.https://www.tandfonline.com/doi/10.1080/10095020.2024.2449458International trade network (ITN)spatial-temporal analysisresearch frameworktopology analysisstructure predictioncorrelation analysis |
| spellingShingle | Donghai Liu Ziwen Yang Kun Qin Kai Li Spatial-temporal analysis of the international trade network Geo-spatial Information Science International trade network (ITN) spatial-temporal analysis research framework topology analysis structure prediction correlation analysis |
| title | Spatial-temporal analysis of the international trade network |
| title_full | Spatial-temporal analysis of the international trade network |
| title_fullStr | Spatial-temporal analysis of the international trade network |
| title_full_unstemmed | Spatial-temporal analysis of the international trade network |
| title_short | Spatial-temporal analysis of the international trade network |
| title_sort | spatial temporal analysis of the international trade network |
| topic | International trade network (ITN) spatial-temporal analysis research framework topology analysis structure prediction correlation analysis |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2024.2449458 |
| work_keys_str_mv | AT donghailiu spatialtemporalanalysisoftheinternationaltradenetwork AT ziwenyang spatialtemporalanalysisoftheinternationaltradenetwork AT kunqin spatialtemporalanalysisoftheinternationaltradenetwork AT kaili spatialtemporalanalysisoftheinternationaltradenetwork |