Analysis of factors associated with Grant for PCT national phase entries patent: a mathematical model

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

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