Title: Innovation output estimation method for a national innovation system: application to the BRICS countries
Authors: Luciele Cristina Pelicioni; Joana Ramos Ribeiro; Rodrigo Arnaldo Scarpel; Tessaleno Devezas; Mischel Carmen Neyra Belderrain; Francisco Cristovão Lourenço De Melo
Addresses: Instituto Tecnológico de Aeronáutica (ITA), Praça Marechal Eduardo Gomes, 50 – São José dos Campos/SP, Brazil ' Instituto Tecnológico de Aeronáutica (ITA), Praça Marechal Eduardo Gomes, 50 – São José dos Campos/SP, Brazil ' Instituto Tecnológico de Aeronáutica (ITA), Praça Marechal Eduardo Gomes, 50 – São José dos Campos/SP, Brazil ' Universidade Atlântica – University Higher Institution, Fábrica da Pólvora de Barcarena, 2730-036 Barcarena, Portugal ' Instituto Tecnológico de Aeronáutica (ITA), Praça Marechal Eduardo Gomes, 50 – São José dos Campos/SP, Brazil ' Instituto de Aeronáutica e Espaço (IAE), Praça Marechal Eduardo Gomes, 50 – São José dos Campos/SP, Brazil
Abstract: The evaluation of the ability of a country to promote innovation is a valuable step to assist countries in designing suitable economic policies. A usual approach to perform such evaluation and for ranking countries according to their innovation rate is the usage of innovation indices. However, those indices are not appropriate for evaluating whether a set of countries are producing innovation below of what is expected from them. Thus, the aim of this study was to create a model using structural equation model (SEM) to allow evaluating the innovation capacity of any country and to calculate the expected outputs as a function of the estimated inputs. The model showed that the countries belonging to the BRICS group, except for South Africa, presented outputs close to or above the expected for these countries, achieving a performance similar to the group of countries with negative scores of input and output factors.
Keywords: BRICS; causal relationships; confirmatory factor analysis; global innovation index; innovation capacity performance; innovation output; innovation index; multiple regression; national innovation system; structural equation modelling; SEM.
DOI: 10.1504/IJMDA.2018.091828
International Journal of Multivariate Data Analysis, 2018 Vol.1 No.3, pp.261 - 279
Received: 07 Aug 2017
Accepted: 11 Oct 2017
Published online: 18 May 2018 *