title   
  

A decision support system to evaluate the competitiveness of nations

Önsel, Şule and Ülengin, Füsün and Ulusoy, Gündüz and Kabak, Özgür and Topçu, İlker and Aktaş, Emel (2007) A decision support system to evaluate the competitiveness of nations. In: 12th WSEAS International Conference on Applied Mathematics, Cairo, Egypt

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
516Kb

Abstract

The measurement of competitiveness and strategy development is an important issue for policy makers. The aim of this paper 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, a combined clustering analysis methodology is used to assign countries to appropriate clusters. In current methods, country clustering is generally based on GDP. However, we suggest that GDP alone is insufficient to define the stage of competitiveness a country belongs. In the proposed methodology, 135 criteria are used 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 attribute/criteria weights, which are, for the most part, subjectively specified in existing methods. Finally, in the third step, the countries of interest are ranked based on weights generated in the previous step. Beyond the ranking of countries, the proposed methodology can also be used to identify those attributes that a given country should focus on in order to improve its position relative to other countries, i.e., to transition from its current cluster to the next higher one. As a final analysis, the dynamic change of the rank of the countries over years has also been investigated.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:Ranking, Competitiveness, Artificial Neural Network, Cluster Analysis
Subjects:T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering
ID Code:29309
Deposited By:Gündüz Ulusoy
Deposited On:20 May 2016 16:01
Last Modified:20 May 2016 16:01

Repository Staff Only: item control page