Abstract
The aim of this chapter is to explore methodological transparency as a viable solution to problems created by existing aggregated indices as well as to conduct a detailed analysis on the ongoing performance of nations’ competitiveness. For this purpose, a methodology composed of three steps is used. To start with, a combined clustering analysis methodology is used to assign countries to appropriate clusters. Unlike the current methods that use a single criterion, the proposed methodology uses 135 criteria for a proper classification of the countries. Relationships between the criteria and classification of the countries are determined using artificial neural networks (ANNs). ANN provides an objective method for determining the criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, the countries are ranked based on weights generated in the previous step. As a final analysis, the dynamic change of the rank of the countries over years has also been investigated.
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Önsel, Ş., Ülengin, F., Ulusoy, G., Kabak, Ö., Topcu, Y.İ., Aktaş, E. (2009). A decision support system to evaluate the competitiveness of nations. In: Mastorakis, N., Sakellaris, J. (eds) Advances in Numerical Methods. Lecture Notes in Electrical Engineering, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76483-2_10
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DOI: https://doi.org/10.1007/978-0-387-76483-2_10
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