Scholarlink

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.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Towards a Digital Europe: Modelling Innovation in a Spatially Embedded Context

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Emma Bruno,
  • Rosalia Castellano,
  • Gennaro Punzo,
  • Luca Salvati

摘要

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.