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A new perspective on the competitiveness of nations

  • Önsel, Sule
  • Ülengin, Füsun
  • Ulusoy, Gündüz
  • Aktas, Emel
  • Kabak, Özgür
  • Topcu, Y. Ilker
Registered author(s):

    The capability of firms to survive and to have a competitive advantage in global markets depends on, amongst other things, the efficiency of public institutions, the excellence of educational, health and communications infrastructures, as well as on the political and economic stability of their home country. The measurement of competitiveness and strategy development is thus an important issue for policy-makers. Despite many attempts to provide objectivity in the development of measures of national competitiveness, there are inherently subjective judgments that involve, for example, how data sets are aggregated and importance weights are applied. Generally, either equal weighting is assumed in calculating a final index, or subjective weights are specified. The same problem also occurs in the subjective assignment of countries to different clusters. Developed as such, the value of these type indices may be questioned by users. The aim of this paper is to explore methodological transparency as a viable solution to problems created by existing aggregated indices. For this purpose, a methodology composed of three steps is proposed. To start, a hierarchical clustering analysis 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 for purposes of country clustering. In the proposed methodology, 178 criteria are used for this purpose. Next, 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 our 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.

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    Article provided by Elsevier in its journal Socio-Economic Planning Sciences.

    Volume (Year): 42 (2008)
    Issue (Month): 4 (December)
    Pages: 221-246

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    Handle: RePEc:eee:soceps:v:42:y:2008:i:4:p:221-246
    Contact details of provider: Web page: http://www.elsevier.com/locate/seps

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    1. Oral, Muhittin & Chabchoub, Habib, 1996. "On the methodology of the World Competitiveness Report," European Journal of Operational Research, Elsevier, vol. 90(3), pages 514-535, May.
    2. Oral, Muhittin & Kettani, Ossama & Cosset, Jean-Claude & Daouas, Mohamed, 1992. "An estimation model for country risk rating," International Journal of Forecasting, Elsevier, vol. 8(4), pages 583-593, December.
    3. Nour, Mohamed A. & Madey, Gregory R., 1996. "Heuristic and optimization approaches to extending the Kohonen self organizing algorithm," European Journal of Operational Research, Elsevier, vol. 93(2), pages 428-448, September.
    4. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer, vol. 45(3), pages 325-342, September.
    5. Ulengin, Fusun & Ulengin, Burc & Onsel, Sule, 2002. "A power-based measurement approach to specify macroeconomic competitiveness of countries," Socio-Economic Planning Sciences, Elsevier, vol. 36(3), pages 203-226, September.
    6. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    7. Hruschka, Harald, 1993. "Determining market response functions by neural network modeling: A comparison to econometric techniques," European Journal of Operational Research, Elsevier, vol. 66(1), pages 27-35, April.
    8. Oral, Muhittin & Cinar, Unver & Chabchoub, Habib, 1999. "Linking industrial competitiveness and productivity at the firm level," European Journal of Operational Research, Elsevier, vol. 118(2), pages 271-277, October.
    9. Hwarng, H. Brian & Ang, H. T., 2001. "A simple neural network for ARMA(p,q) time series," Omega, Elsevier, vol. 29(4), pages 319-333, August.
    10. Oral, Muhittin, 1993. "A methodology for competitiveness analysis and strategy formulation in glass industry," European Journal of Operational Research, Elsevier, vol. 68(1), pages 9-22, July.
    11. Oral, Muhittin & Chabchoub, Habib, 1997. "An estimation model for replicating the rankings of the world competitiveness report," International Journal of Forecasting, Elsevier, vol. 13(4), pages 527-537, December.
    12. Zanakis, Stelios H. & Becerra-Fernandez, Irma, 2005. "Competitiveness of nations: A knowledge discovery examination," European Journal of Operational Research, Elsevier, vol. 166(1), pages 185-211, October.
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