Networks, obstacles, and resources for innovative performance: an analysis via neural networks for prediction in the manufacturing industry

• Fernando Barrios Aguirre ^[1] ; Sandra Yaneth Mora Malagón ^[2] ; Martha Isabel Amado Piñeros ^[1] ; Luis Gabriel Gutiérrez Bernal ^[1]
  1. [1] School of Management, Business, and Economics Sciences, University Foundation of the Andean Area, Bogotá, Colombia
  2. [2] School of Economic, University of the Andes, Bogota, Colombia
• Localización: Journal of Technology Management & Innovation, ISSN-e 0718-2724, Vol. 17, Nº. 4, 2022, págs. 40-47
• Idioma: inglés
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• Resumen

  • This document aims to predict the level of innovation in manufacturing companies in Colombia between 2017-2018. A forecasting mechanism for innovation performance has been constructed using Neural Networks (NNs). This model considers the objectives of innovation, obstacles to innovation, knowledge networks, and technical information of each one of the firms. Results show that demand push, vertical sources, financial obstacles, and qualified personnel are the most important variables in predicting innovative performance. Our empirical analysis uses firm-level innovation survey data from the EDIT (Encuesta de Desarrollo e Innovación Tecnológica in Spanish, Technological Development, and Innovation Survey in English) for Colombia for the years 2017-2018.