Title: Innovation and efficiency in Latin American countries: a study of the impact and applied evolution of neural networks

Authors: Mercedes Gaitán-Angulo; Melva Inés Gómez-Caicedo; Anderson Quintero; Juan Antonio Marmolejo Martín; Hasbleidy Camila Parra Méndez; Carlos Yesid Briñez Torres

Addresses: Business School, Konrad Lorenz University Foundation, Bogotá, Colombia ' School of Economics, Administrative and Accounting Sciences, Fundación Universitaria los Libertadores, Bogotá, Colombia ' Faculty of Mathematics and Engineering, Konrad Lorenz University Foundation, Bogotá, Colombia ' Faculty of Mathematics, University of Granada, Granada, Spain ' Business School, Konrad Lorenz University Foundation, Bogotá, Colombia ' Faculty of Mathematics, Universidad Piloto de Colombia, Bogotá, Colombia

Abstract: The relationship between the indicators that measure innovation and efficiency in Latin America is of vital importance, as it allows for the acquisition of valuable information for the implementation of strategies that promote development in the region. The main contribution of this work is to identify the constructs that enhance the innovative characteristics of these Latin American countries before the world. The relevant characteristics were identified according to the Global Innovation Index data from 2013 to 2020. We used principal component analysis, and then a simulation is performed from 2021 to 2030 using neural networks, which allows us to identify better innovative policies based on the region's resources focused on its socio-economic structure. Among the main findings, we find that the region's best performance is concentrated in the following pillars: institutions and infrastructure and knowledge and technology products. However, problems are evident in human capital formation, market satisfaction, business satisfaction and creative production.

Keywords: innovation; knowledge management; Global Innovation Index; GII; Latin America; neural networks.

DOI: 10.1504/IJRM.2023.134677

International Journal of Revenue Management, 2023 Vol.13 No.4, pp.257 - 280

Received: 03 May 2022
Accepted: 27 Oct 2022
Published online: 03 Nov 2023 *

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