Cluster Analysis for Foreign Trade Data: The Case of Turkey, Azerbaijan, and Kazakhstan

Creative Commons License

Cilgin C., KURT A. S.

SOSYOEKONOMI, cilt.29, sa.48, ss.511-540, 2021 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 48
  • Basım Tarihi: 2021
  • Doi Numarası: 10.17233/sosyoekonomi.2021.02.24
  • Dergi Adı: SOSYOEKONOMI
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.511-540
  • Anahtar Kelimeler: Foreign Trade, Clustering, K-Means, Ward Hierarchical Clustering, Self-Organizing Maps (SOM)
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

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.