A new perspective on the competitiveness of nations

dc.authoridTR143828en_US
dc.authoridTR13259en_US
dc.authoridTR48345en_US
dc.authoridTR149435en_US
dc.contributor.authorÖnsel Ekici, Şule
dc.contributor.authorÜlengin, Füsun
dc.contributor.authorUlusoy, Gündüz
dc.contributor.authorAktaş, Emel
dc.contributor.authorKabak, Özgür
dc.contributor.authorTopçu, Yusuf İlker
dc.date.accessioned2015-11-18T14:07:42Z
dc.date.available2015-11-18T14:07:42Z
dc.date.issued2008
dc.departmentDoğuş Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.descriptionÖnsel, Şule (Dogus Author) -- Ülengin, Füsun (Dogus Author)en_US
dc.description.abstractThe 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.en_US
dc.identifier.citationÖnsel, Ş., Ülengin, F., Ulusoy, G., Aktaş, E., Kabak, Ö., & Topçu, Y. İ. (2008). A new perspective on the competitiveness of nations. Socio-Economic Planning Sciences, 42(4), 221-246. https://dx.doi.org/10.1016/j.seps.2007.11.001en_US
dc.identifier.doi10.1016/j.seps.2007.11.001
dc.identifier.endpage246en_US
dc.identifier.issn0038-0121
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-51449122021en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage221en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.seps.2007.11.001
dc.identifier.urihttps://hdl.handle.net/11376/2198
dc.identifier.volume42en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÖnsel, Şule
dc.institutionauthorÜlengin, Füsun
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofSocio-Economic Planning Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectCluster Analysisen_US
dc.subjectCompetitivenessen_US
dc.subjectRankingen_US
dc.titleA new perspective on the competitiveness of nationsen_US
dc.typeArticleen_US

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