This study explores the effects of firms’ investments in using highly disruptive technologies in the energy sector on the EU-27 over the 1990-2019 period. An Artificial Neural Networks (ANNs) experiment through a Deep Learning (DL) approach is implemented to test this hypothesis. The empirical findings show that investments in highly disruptive technologies boost economic growth. In addition, a positive association between trade and output is confirmed. The expected benefits represent a possible policy measure to offset the decline in global activity due to the impact of the war in Ukraine on global energy markets. They also represent a crucial driver of digitalization, implying a radical innovation in business models, completely transforming the market. Finally, promising policy actions are discussed.
The role of circular economy in EU entrepreneurship: A deep learning experiment
Morelli, Giovanna;
2024-01-01
Abstract
This study explores the effects of firms’ investments in using highly disruptive technologies in the energy sector on the EU-27 over the 1990-2019 period. An Artificial Neural Networks (ANNs) experiment through a Deep Learning (DL) approach is implemented to test this hypothesis. The empirical findings show that investments in highly disruptive technologies boost economic growth. In addition, a positive association between trade and output is confirmed. The expected benefits represent a possible policy measure to offset the decline in global activity due to the impact of the war in Ukraine on global energy markets. They also represent a crucial driver of digitalization, implying a radical innovation in business models, completely transforming the market. Finally, promising policy actions are discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
