TY  - JOUR
A1  - ,  
T1  - Analysis of factors associated with Grant for PCT national phase entries patent: a mathematical model
JO  - Eur. J. Anat.
SN  - 1136-4890
Y1  - 2019
VL  - 23
SP  - 333
EP  - 340
UR  - http://www.eurjanat.com/web/paper.php?id=190233ap
KW  - Patents multidisciplinary analysis â?? Quality Signal
KW  - Research and Development â?? Pa-tent indicator â?? Patent statistics â?? Multivariate line-ar regression model
N2  - 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 varia-bles. 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 patent-ability are qualified R&D personnel.
ER  -