We investigate the innovational determinants of “Patent Applications” in Europe. We usedata from the European Innovation Scoreboard-EIS of the European Commission for 36countries in the period 2010- 2019. We use Panel Data with Fixed Effects, Panel Data withRandom Effects, Pooled OLS, WLS and Dynamic Panel. We found that the variables that have adeeper positive association with “Patent Applications” are “Human Resources” and“Intellectual Assets”, while the variables that show a more intense negative relation with PatentApplications are “Employment Share in Manufacturing” and “Total Entrepreneurial Activity”.A cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient has beenrealized. The results show the presence of two clusters. A network analysis with the distance ofManhattan has been performed and we find three different complex network structures. Finally,a comparison is made among eight machine learning algorithms for the prediction of the futurevalue of the “Patent Applications”. We found that PNN-Probabilistic Neural Network is the bestperforming algorithm. (PDF) The Impact of Patent Applications on Technological Innovation in European Countries. Available from: https://www.researchgate.net/publication/380315790_The_Impact_of_Patent_Applications_on_Technological_Innovation_in_European_Countries [accessed May 07 2024].
The Impact of Patent Applications on Technological Innovation in European Countries
Lucio Laureti
;Alberto Costantiello
;Fabio Anobile
;
2024-01-01
Abstract
We investigate the innovational determinants of “Patent Applications” in Europe. We usedata from the European Innovation Scoreboard-EIS of the European Commission for 36countries in the period 2010- 2019. We use Panel Data with Fixed Effects, Panel Data withRandom Effects, Pooled OLS, WLS and Dynamic Panel. We found that the variables that have adeeper positive association with “Patent Applications” are “Human Resources” and“Intellectual Assets”, while the variables that show a more intense negative relation with PatentApplications are “Employment Share in Manufacturing” and “Total Entrepreneurial Activity”.A cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient has beenrealized. The results show the presence of two clusters. A network analysis with the distance ofManhattan has been performed and we find three different complex network structures. Finally,a comparison is made among eight machine learning algorithms for the prediction of the futurevalue of the “Patent Applications”. We found that PNN-Probabilistic Neural Network is the bestperforming algorithm. (PDF) The Impact of Patent Applications on Technological Innovation in European Countries. Available from: https://www.researchgate.net/publication/380315790_The_Impact_of_Patent_Applications_on_Technological_Innovation_in_European_Countries [accessed May 07 2024].I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
