Leila Mirtajadini, Shamsollah Shirin Bakhsh, M. Mousavi, Kioumars Heydari, S. Yousefvand
{"title":"基于网络理论的电力贸易伙伴预测——以西亚共同体为例","authors":"Leila Mirtajadini, Shamsollah Shirin Bakhsh, M. Mousavi, Kioumars Heydari, S. Yousefvand","doi":"10.1177/00157325231166242","DOIUrl":null,"url":null,"abstract":"This study aims to predict electricity cross-border trade partners based on the network theory and to investigate the position and importance of West Asia community in the global electricity trade network. For this purpose, the global network is constructed to examine the role of each node in the network for the time period of 2010–2018. Different communities are identified to proceed with the network analysis. The innovative analysis is link prediction to forecast missing links from the network. The results suggest more interconnectedness among community members, especially Iran, Turkey and Russia, which are the prominent nodes in the community. The link prediction outcomes offer the most probable missing links from the community and lead us to select the common neighbour approach as the most efficient method. JEL Codes: D85, Q27","PeriodicalId":29933,"journal":{"name":"Foreign Trade Review","volume":"9 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of Electricity Trade Partners Based on the Network Theory: The West Asia Community\",\"authors\":\"Leila Mirtajadini, Shamsollah Shirin Bakhsh, M. Mousavi, Kioumars Heydari, S. Yousefvand\",\"doi\":\"10.1177/00157325231166242\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to predict electricity cross-border trade partners based on the network theory and to investigate the position and importance of West Asia community in the global electricity trade network. For this purpose, the global network is constructed to examine the role of each node in the network for the time period of 2010–2018. Different communities are identified to proceed with the network analysis. The innovative analysis is link prediction to forecast missing links from the network. The results suggest more interconnectedness among community members, especially Iran, Turkey and Russia, which are the prominent nodes in the community. The link prediction outcomes offer the most probable missing links from the community and lead us to select the common neighbour approach as the most efficient method. JEL Codes: D85, Q27\",\"PeriodicalId\":29933,\"journal\":{\"name\":\"Foreign Trade Review\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Foreign Trade Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/00157325231166242\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Foreign Trade Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/00157325231166242","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS","Score":null,"Total":0}
Prediction of Electricity Trade Partners Based on the Network Theory: The West Asia Community
This study aims to predict electricity cross-border trade partners based on the network theory and to investigate the position and importance of West Asia community in the global electricity trade network. For this purpose, the global network is constructed to examine the role of each node in the network for the time period of 2010–2018. Different communities are identified to proceed with the network analysis. The innovative analysis is link prediction to forecast missing links from the network. The results suggest more interconnectedness among community members, especially Iran, Turkey and Russia, which are the prominent nodes in the community. The link prediction outcomes offer the most probable missing links from the community and lead us to select the common neighbour approach as the most efficient method. JEL Codes: D85, Q27
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