A novel approach for predicting global innovation index scores

Rabia Sultan Yildirim, Mülayim Ongun Ukelge, Esra Sarac Essiz and Murat Oturakci

International Journal of Applied Management Science, 2024, vol. 16, issue 3, 239-260

Abstract: Innovation 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.

Keywords: global innovation index; feature selection; ANN; artificial neural network. (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ids:injams:v:16:y:2024:i:3:p:239-260

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