A novel approach for predicting global innovation index scores

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dc.contributor.authorYildirim, Rabia Sultan
dc.contributor.authorUkelge, Mulayim Ongun
dc.contributor.authorEssiz, Esra Sarac
dc.contributor.authorOturakci, Murat
dc.date.accessioned2025-01-06T17:38:10Z
dc.date.available2025-01-06T17:38:10Z
dc.date.issued2024
dc.description.abstractInnovation has great importance in growth models in today's economy. In the globalising world, countries that renew their product and service range are at the forefront. The way to manage innovation is to measure it. Therefore, to have measurable information, the Global Innovation Index (GII) identifies inputs and outputs that are indicators of innovation. The GII provides a global ranking for countries according to their innovation capacity. In this study, GII scores of 125 countries between the years 2013 and 2020 were estimated using the artificial neural network (ANN). Before the estimation, feature selection was performed from 61 common indicator parameters. 27 parameters that best explain the GII score were selected and used in the ANN. According to the estimated GII scores, the selected 27 parameters are sufficient to calculate the GII score and has been observed that the ANN model is sufficient to determine the approximate GII score of the countries.
dc.identifier.doi10.1504/IJAMS.2024.140047
dc.identifier.issn1755-8913
dc.identifier.issn1755-8921
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85199324007
dc.identifier.scopusqualityQ4
dc.identifier.urihttps://doi.org/10.1504/IJAMS.2024.140047
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2504
dc.identifier.volume16
dc.identifier.wosWOS:001272232300001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInderscience Enterprises Ltd
dc.relation.ispartofInternational Journal of Applied Management Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectglobal innovation index
dc.subjectfeature selection
dc.subjectANN
dc.subjectartificial neural network
dc.titleA novel approach for predicting global innovation index scores
dc.typeArticle

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