Cluster Analysis for Foreign Trade Data: The Case of Turkey, Azerbaijan, and Kazakhstan
SOSYOEKONOMI, vol.29, no.48, pp.511-540, 2021 (ESCI, Scopus, TRDizin)
- Publication Type: Article / Article
- Volume: 29 Issue: 48
- Publication Date: 2021
- Doi Number: 10.17233/sosyoekonomi.2021.02.24
- Journal Name: SOSYOEKONOMI
- Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, TR DİZİN (ULAKBİM)
- Page Numbers: pp.511-540
- Keywords: Foreign Trade, Clustering, K-Means, Ward Hierarchical Clustering, Self-Organizing Maps (SOM)
- Open Archive Collection: AVESIS Open Access Collection
- Dokuz Eylül University Affiliated: Yes
Abstract
Foreign trade is one of the most critical sources of welfare. Factors such as population, per capita income, and the distance between countries is among the crucial determinants of foreign trade. This paper aims to cluster the data set regarding the export and import of Turkey and Turkic Republics by considering other determinants of foreign trade for 2017. In this study, Kazakhstan and Azerbaijan, of which data sets are available, are considered, and Turkey. For this paper, K-means, Ward hierarchical clustering, and self-organizing maps are used. The findings of this paper present detailed evidence as to the export and import of the countries handled.