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Revealing the importance of international and domestic cooperation by using artificial neural networks: case of European radical and incremental innovators

Viktor Prokop (Univerzita Pardubice, Pardubice, Czech Republic)
Jan Stejskal (Univerzita Pardubice, Pardubice, Czech Republic)
Beata Mikusova Merickova (Matej Bel University, Banska Bystrica, Slovakia)
Samuel Amponsah Odei (Department of Economics, University of Hradec Kralove, Hradec Kralove, Czech Republic)

European Journal of Innovation Management

ISSN: 1460-1060

Article publication date: 20 September 2021

Issue publication date: 8 March 2023




The purpose of this study is to introduce innovative ideas into the treatment of the radical and incremental innovations and to fill the research gap by using: (1) methods that can perform complicated tasks and solve complex problems leading in creation of radical and incremental innovation and (2) a broad sample of firms across countries. The authors’ ambition is to contribute to the scientific knowledge by producing evidence about the novel usage of artificial neural network techniques for measuring European firms' innovation activities appearing in black boxes of innovation processes.


In this study, the authors incorporate an international context into Chesbrough's open innovation (OI) theory and, on the one hand, support the hypothesis that European radical innovators benefit more from foreign cooperation than incremental innovators. On the other hand, the results of the analyses show that European incremental innovators rely on domestic cooperation supported by cooperation with foreign public research institutes. Moreover, the use of decision trees (DT) allows the authors to reveal specific patterns of successful innovators emerging within the hidden layers of neural networks.


The authors prove that radical European innovators using either internal or external R&D strategies, while the combinations of these strategies do not bring successful innovation outputs. In contrast, European incremental innovators benefit from various internal R&D processes in which engagement in design activities plays a crucial role.


The authors introduce innovative ideas into the treatment of hidden innovation processes and measuring the innovation performance (affected by domestic or international cooperation) of European firms. The approach places emphasis on the novelty of innovation and the issue of international cooperation in the era of OI by designing the framework using a combination of artificial neural networks and DT.



This work was supported by a grant provided by the scientific research project of the Czech Sciences Foundation Grant No. 20-03037S.


Prokop, V., Stejskal, J., Mikusova Merickova, B. and Odei, S.A. (2023), "Revealing the importance of international and domestic cooperation by using artificial neural networks: case of European radical and incremental innovators", European Journal of Innovation Management, Vol. 26 No. 2, pp. 531-563.



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