Measuring the Importance of Innovation in Portuguese Economic Development

Cicero Eduardo Walter (), Manuel Au-Yong-Oliveira () and Marcos Ferasso ()
Additional contact information
Cicero Eduardo Walter: GOVCOPP, University of Aveiro
Manuel Au-Yong-Oliveira: University of Aveiro
Marcos Ferasso: Lusófona University. Campo Grande

Journal of the Knowledge Economy, 2025, vol. 16, issue 3, No 77, 13145 pages

Abstract: Abstract Under the assumption that innovation and the processes of technological change are crucial to economic development, this research sought to measure the relative importance of innovation for economic development in Portugal. To this end, data were collected from official statistics produced by the government of Portugal and the European Union, primarily from the Pordata, Eurostat, and Directorate-General for Statistics of Education and Science databases. The statistical technique used in the present investigation was random forest, best exemplified as a supervised machine learning algorithm. The results suggest that R&D expenditure and its outcomes — patent and design/model applications and grants — contribute to Portuguese economic development, mainly through an upward gradient relationship. In addition, our research provides evidence that product and process innovations are marginally positioned in the hierarchy of importance for Portuguese economic development when analyzed in conjunction with other innovation inputs and outputs. These results provide evidence that the Portuguese National Innovation System has been configured in a disjointed manner, especially concerning the development of structured stimuli that foster the emergence of innovations with real impacts on Portuguese economic development. This study contributes to the literature by highlighting the need for more synergy within Portugal’s National Innovation System. Future research should explore the mechanisms through which product and process innovations can significantly impact economic development.

Keywords: Innovation; Economic development; Portugal; Machine learning; Random forest (search for similar items in EconPapers)
JEL-codes: O11 O31 O32 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13132-024-02446-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jknowl:v:16:y:2025:i:3:d:10.1007_s13132-024-02446-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/13132

DOI: 10.1007/s13132-024-02446-2

Access Statistics for this article

Journal of the Knowledge Economy is currently edited by Elias G. Carayannis

More articles in Journal of the Knowledge Economy from Springer, Portland International Center for Management of Engineering and Technology (PICMET)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().