Analysis of factors associated with Grant for PCT national phase entries patent: a mathematical model
Eur. j. anat
; 23(5): 333-340, sept. 2019. graf, tab
Artigo
em Inglês
| IBECS
| ID: ibc-183863
Biblioteca responsável:
ES1.1
Localização: BNCS
ABSTRACT
We developed a multivariate linear regression model to analyze factors associated with Grant for PCT national phase entries patent, in order to identify patentability success indicators. Information was gathered from the Eurostat and World Intellectual Property Indicators databases (period 2004-2014). Thre regression model were constructed using as response variable Grant for PCT national phase entries patent in the national phase and considering 11 variables related to R&D funding and research personnel as predictor variables. Multivariate linear regression models were estimated using the Bayesian Information Criterion (BIC). The most influential predictive variables were Total R&D personnel and researchers by performance sectors, sex and fields of science. The regression coefficient was 0.001 with (P <0.05). In conclusion, the mathematical model shows that the most effective predictors of patentability are qualified R&D personnel
RESUMEN
No disponible
Texto completo:
Disponível
Coleções:
Bases de dados nacionais
/
Espanha
Base de dados:
IBECS
Assunto principal:
Patentes como Assunto
/
Ciência
/
Modelos Teóricos
Idioma:
Inglês
Revista:
Eur. j. anat
Ano de publicação:
2019
Tipo de documento:
Artigo
Instituição/País de afiliação:
Biohealth Research Institute in Granada (ibs.GRANADA)/Spain
/
Office of Technological Transference of the Public Health System of Andalusia/Spain
/
Servicio Andaluz de Salud/Spain