Title: A novel approach for predicting global innovation index scores

Authors: Rabia Sultan Yildirim; Mülayim Ongun Ukelge; Esra Sarac Essiz; Murat Oturakci

Addresses: Industrial Engineering Department, Adana Alparslan Türkeş Science and Technology University, Adana, Turkey ' Faculty of Management, Adana Alparslan Türkeş Science and Technology University, Adana, Turkey ' Computer Engineering Department, Adana Alparslan Türkes Science and Technology University, Adana, Turkey ' Department of Industrial Engineering, İzmir Bakırçay University, İzmir, Turkey

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.

DOI: 10.1504/IJAMS.2024.140047

International Journal of Applied Management Science, 2024 Vol.16 No.3, pp.239 - 260

Received: 06 Nov 2023
Accepted: 28 Feb 2024
Published online: 16 Jul 2024 *

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