Seyed Arash Shahraeini, S. Tabrizi, C. Spulbar, Ramona Birau, Amir Karbassi Yazdi
{"title":"基于绩效标准的出口信贷机构聚类的新数据挖掘方法:2005 - 2020年文献计量引用分析","authors":"Seyed Arash Shahraeini, S. Tabrizi, C. Spulbar, Ramona Birau, Amir Karbassi Yazdi","doi":"10.52846/ami.v48i1.1579","DOIUrl":null,"url":null,"abstract":"Nowadays, ECAs have a crucial role in the export of production, creating job opportunities for countries and growth of economic indicators.This research aims first to estimate the performance of ECAs based on covering all countries of the world and ranking the countries based on the issue of export credit according to their performance and clustering techniques. For evaluation performance of these ECAs, clustering techniques are used to put them in the categories according to their performance between 2005 to 2020 in the fourth quarter. The context of clustering shows the rank of each cluster, and then exporters can choose a better choice from them. Moreover, for reinsurance,other ECAs can find out which ECAs have high performance. The result indicates that ranking the ECAs and show the performance of each cluster.","PeriodicalId":43654,"journal":{"name":"Annals of the University of Craiova-Mathematics and Computer Science Series","volume":"1 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New Data Mining approach for clustering Export Credit Agencies (ECAs) based on performance criteria: a bibliometric citation analysis for the period 2005 to 2020\",\"authors\":\"Seyed Arash Shahraeini, S. Tabrizi, C. Spulbar, Ramona Birau, Amir Karbassi Yazdi\",\"doi\":\"10.52846/ami.v48i1.1579\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, ECAs have a crucial role in the export of production, creating job opportunities for countries and growth of economic indicators.This research aims first to estimate the performance of ECAs based on covering all countries of the world and ranking the countries based on the issue of export credit according to their performance and clustering techniques. For evaluation performance of these ECAs, clustering techniques are used to put them in the categories according to their performance between 2005 to 2020 in the fourth quarter. The context of clustering shows the rank of each cluster, and then exporters can choose a better choice from them. Moreover, for reinsurance,other ECAs can find out which ECAs have high performance. The result indicates that ranking the ECAs and show the performance of each cluster.\",\"PeriodicalId\":43654,\"journal\":{\"name\":\"Annals of the University of Craiova-Mathematics and Computer Science Series\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2021-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of the University of Craiova-Mathematics and Computer Science Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52846/ami.v48i1.1579\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of the University of Craiova-Mathematics and Computer Science Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52846/ami.v48i1.1579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS","Score":null,"Total":0}
New Data Mining approach for clustering Export Credit Agencies (ECAs) based on performance criteria: a bibliometric citation analysis for the period 2005 to 2020
Nowadays, ECAs have a crucial role in the export of production, creating job opportunities for countries and growth of economic indicators.This research aims first to estimate the performance of ECAs based on covering all countries of the world and ranking the countries based on the issue of export credit according to their performance and clustering techniques. For evaluation performance of these ECAs, clustering techniques are used to put them in the categories according to their performance between 2005 to 2020 in the fourth quarter. The context of clustering shows the rank of each cluster, and then exporters can choose a better choice from them. Moreover, for reinsurance,other ECAs can find out which ECAs have high performance. The result indicates that ranking the ECAs and show the performance of each cluster.