Since Schumpeter’s pioneering studies, the regional dimension of innovation has gained recognition to the extent of being valued within policy frameworks. Grounded in the Triple Helix model, which considers academia, industry, and government, and expanded to include digitalisation, this paper investigates the factors influencing regional innovation in Europe. Through a series of research hypotheses, the study explores whether and to what extent regional innovation depends on local characteristics and how it is influenced by the innovation of neighbouring regions, while accounting for spatial heterogeneity. The estimation strategy is given by GWR-SAR models, which address spatial autocorrelation and spatial heterogeneity simultaneously. The models are estimated for 2017 and 2022 using data on 233 NUTS-2 regions from the 2023 Regional Innovation Scoreboard. The results suggest that digitalisation does not linearly impact innovation. While digitalisation enhances innovation performance, a turning point is reached beyond which further digitalisation yields diminishing returns or even adverse effects on regional innovation.

Innovation and digitalisation in European regions: addressing spatial issues through GWR-SAR approach / Bruno, E.; Castellano, R.; Punzo, G.; Salvati, L.. - In: ANNALS OF OPERATIONS RESEARCH. - ISSN 0254-5330. - (2025). [10.1007/s10479-025-06749-8]

Innovation and digitalisation in European regions: addressing spatial issues through GWR-SAR approach

Salvati L.
2025

Abstract

Since Schumpeter’s pioneering studies, the regional dimension of innovation has gained recognition to the extent of being valued within policy frameworks. Grounded in the Triple Helix model, which considers academia, industry, and government, and expanded to include digitalisation, this paper investigates the factors influencing regional innovation in Europe. Through a series of research hypotheses, the study explores whether and to what extent regional innovation depends on local characteristics and how it is influenced by the innovation of neighbouring regions, while accounting for spatial heterogeneity. The estimation strategy is given by GWR-SAR models, which address spatial autocorrelation and spatial heterogeneity simultaneously. The models are estimated for 2017 and 2022 using data on 233 NUTS-2 regions from the 2023 Regional Innovation Scoreboard. The results suggest that digitalisation does not linearly impact innovation. While digitalisation enhances innovation performance, a turning point is reached beyond which further digitalisation yields diminishing returns or even adverse effects on regional innovation.
2025
NUTS2 regions ; nnovation; Spatial autocorrelation; Spatial heterogeneity; GWR-SAR model
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Innovation and digitalisation in European regions: addressing spatial issues through GWR-SAR approach / Bruno, E.; Castellano, R.; Punzo, G.; Salvati, L.. - In: ANNALS OF OPERATIONS RESEARCH. - ISSN 0254-5330. - (2025). [10.1007/s10479-025-06749-8]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1745458
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