Suchergebnisse

This paper demonstrates the use of Multidimensional Data Analysis methods in revealing latent groups of European countries trading cultural goods over a period of fourteen years (2002-2015). The methods of Multiple Correspondence Analysis (MCA) and Hierarchical Cluster Analysis (HC) are applied on a multivariate matrix that takes into account not only imports and exports of such goods, but in a supplementary way, basic economic and educational variables, in order to detect and explore relationships among them. Furthermore, cluster analysis on MCA results is used to identify all groups of country-years sharing similar characteristics. ; site as: Koutsoupias Nikos, & Boutsiouki Sofia. (2018). Exploring European Cultural Goods Trade: A Multidimensional Perspective. Proceedings of the International Conference of International Business 2017 (ICIB 2017), Thessaloniki, Greece, 19 - 22 May 2017. http://doi.org/10.5281/zenodo.1286354site

This case demonstrates the combined use of Multiple Correspondence Analysis and Hierarchical Clustering on metadata from articles of Perceptions: Journal of International Affair? published in English under the auspices of the Centre for Strategic Research, an organization connected to Turke?u?s ministry of foreign affairs. A period of 3?years (20102012) is covered, with 58 articles. In particular, the case links the quantitative analysis of scientific discours??through specific tools of multivariate data analysi?with research on the development of the Politics and International Relations scientific field.