Developing Statistical Optimization Models for Urban Competitiveness Index: Under the Boundaries of Econophysics Approach

MakaleAçık ErişimScopus SJRQ1
  • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar

Özet

The purpose of this research was to establish the urban competitiveness index (UCI) by using the statistical optimization method for the econophysics approach. With this technique, economic data regarding urban areas and the factors affecting UCI have been determined. The research covers 30 urban centres located in 15 countries worldwide. Urban centres with the gross domestic product per capita of $10,000 or more were taken into consideration. The significant levels of the factors were determined with the statistical optimization method, and optimum values were calculated with the developed optimization models. Re-index values were calculated and compared with the results of PricewaterhouseCoopers and World Economic Forum. According to the results, the high UCI value of these locations depends not only on economic data but also on high values of social factors. Thus, those locations are becoming the centre of attraction for investments and capital with increasing competitiveness.

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/bayburt/12342Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1155/2019/4053970Yayıncı resmi DOI adresi
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Scopus
5
WoS
4
OpenAlex
9
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorDönmez, Cem Çaǧri
dc.contributor.authorAtalan, Abdulkadir
dc.contributor.authorLocurcio, Marco
dc.date.accessioned2026-10-29T19:09:27.920202026Z
dc.date.available2026-10-29T19:09:27.920202026Z
dc.date.issued2019
dc.description.abstractThe purpose of this research was to establish the urban competitiveness index (UCI) by using the statistical optimization method for the econophysics approach. With this technique, economic data regarding urban areas and the factors affecting UCI have been determined. The research covers 30 urban centres located in 15 countries worldwide. Urban centres with the gross domestic product per capita of $10,000 or more were taken into consideration. The significant levels of the factors were determined with the statistical optimization method, and optimum values were calculated with the developed optimization models. Re-index values were calculated and compared with the results of PricewaterhouseCoopers and World Economic Forum. According to the results, the high UCI value of these locations depends not only on economic data but also on high values of social factors. Thus, those locations are becoming the centre of attraction for investments and capital with increasing competitiveness.
dc.identifier.articlenumber4053970
dc.identifier.doi10.1155/2019/4053970
dc.identifier.eissn1099-0526
dc.identifier.issn1076-2787
dc.identifier.scopus2-s2.0-85076347063
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/12342
dc.identifier.volume2019
dc.identifier.wosWOS:000501207700005
dc.language.isoen
dc.publisherHindawi Limited
dc.relation.ispartofComplexity
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subject.classificationMathematics, Interdisciplinary Applications
dc.subject.classificationMultidisciplinary Sciences
dc.subject.classificationMathematics
dc.subject.classificationScience & Technology - Other Topics
dc.subject.otherOptimization
dc.subject.otherEconomic data
dc.subject.otherEconophysicss
dc.subject.otherGross domestic products
dc.subject.otherOptimization models
dc.subject.otherPricewaterhouseCoopers
dc.subject.otherSocial factor
dc.subject.otherStatistical optimization
dc.subject.otherUrban competitiveness
dc.subject.otherCompetition
dc.titleDeveloping Statistical Optimization Models for Urban Competitiveness Index: Under the Boundaries of Econophysics Approach
dc.typeArticle
rdl.citation.openalex9
rdl.citation.scopus5
rdl.citation.wos4
rdl.oa.statusgold
rdl.oa.urlhttps://downloads.hindawi.com/journals/complexity/2019/4053970.pdf
rdl.scopus.quartileQ1
rdl.sdgSDG11
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)
rdl.wos.indexSocial Science Citation Index (SSCI)