This study investigates the primary drivers of innovation processes in Europe within a broad framework that embraces the digitalisation dimension. Using data from the Regional Innovation Scoreboard (2017 and 2022), Spatial Autoregressive – Geographically Weighted Regression (GWR-SAR) models are performed to address spatial dependence and spatial heterogeneity simultaneously. An inverted U-shaped relationship suggests a nonlinear impact of digitalisation and technological advancements on regional innovation, emphasising the importance of balancing digital skills with other factors to maximise their benefits.
Towards a digital Europe: Modelling innovation in a spatially embedded context integrated space-time model to evaluate the innovation drivers in Italy
Emma Bruno
;Rosalia Castellano;Gennaro Punzo;
2024-01-01
Abstract
This study investigates the primary drivers of innovation processes in Europe within a broad framework that embraces the digitalisation dimension. Using data from the Regional Innovation Scoreboard (2017 and 2022), Spatial Autoregressive – Geographically Weighted Regression (GWR-SAR) models are performed to address spatial dependence and spatial heterogeneity simultaneously. An inverted U-shaped relationship suggests a nonlinear impact of digitalisation and technological advancements on regional innovation, emphasising the importance of balancing digital skills with other factors to maximise their benefits.File in questo prodotto:
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