Innovative Clusters of Global Trade Leadership Cover Image

Innovative Clusters of Global Trade Leadership
Innovative Clusters of Global Trade Leadership

Author(s): Liudmyla Tsymbal, Nataliya Moskalyuk, Svitlana Gromenkova, Vitaliy Chaban
Subject(s): Economy, Business Economy / Management
Published by: Wydawnictwo Uniwersytetu Łódzkiego
Keywords: Index of economic complexity; intellectualization; clustering of countries; commodity exports

Summary/Abstract: The formation of a new global system and systemic global interdependence has generated new competitiveness factors for market participants, determining their appropriate strategic behavior to ensure a highly competitive position and leadership. Therefore, the purpose of the study is to identify the countries of intellectual leaders in the global market and the factors that influence the positions that countries achieve in terms of leadership. The following research methods were used: multifactor regression models, cluster analysis, and comparative analysis. Based on the authors’ methodology for assessing countries’ intellectual leadership, the clustering of countries in the global economy is determined. The evaluation algorithm was based on three levels: 1) resources, 2) the intermediate results of intellectual activity, and 3) the final results of overall progress. Using a multifactor regression model and cluster analysis, four clusters of countries were identified according to key indicators of intellectual leadership. For each cluster, the specialization of the two countries in terms of merchandise exports was analyzed: cluster 1 – the United States and Germany; cluster 2 – Israel and Italy; cluster 3 – Brazil and Ukraine; cluster 4 – China and South Korea. Each country is assigned an index of economic complexity, and the change in position of each country within a cluster over ten years is noted. An important goal is to understand the determinants of the leadership of countries in each geographic region. The analysis is based on the cluster analysis carried out in previous publications. The clustering of countries was carried out based on the dynamics of macroeconomic indicators over the past 15 years.

  • Issue Year: 26/2023
  • Issue No: 2
  • Page Range: 71-84
  • Page Count: 14
  • Language: English