European Union Innovation Efficiency Assessment Based on Data Envelopment Analysis

Meda Andrijauskiene (), Dimosthenis Ioannidis, Daiva Dumciuviene, Asimina Dimara, Napoleon Bezas, Alexios Papaioannou and Stelios Krinidis
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Meda Andrijauskiene: School of Economics and Business, Kaunas University of Technology, LT-44029 Kaunas, Lithuania
Dimosthenis Ioannidis: Centre for Research and Technology (CERTH)—Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece
Daiva Dumciuviene: School of Economics and Business, Kaunas University of Technology, LT-44029 Kaunas, Lithuania
Asimina Dimara: Centre for Research and Technology (CERTH)—Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece
Napoleon Bezas: Centre for Research and Technology (CERTH)—Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece
Alexios Papaioannou: Centre for Research and Technology (CERTH)—Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece
Stelios Krinidis: Centre for Research and Technology (CERTH)—Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece

Economies, 2023, vol. 11, issue 6, 1-19

Abstract: Though much attention is dedicated to the development of its research and innovation policy, the European Union constantly struggles to match the level of the strongest innovators in the world. Therefore, there is a necessity to analyze the individual efforts and conditions of the 27 member states that might determine their final innovative performance. The results of a scientific literature review showed that there is a growing interest in the usage of artificial intelligence when seeking to improve decision-making processes. Data envelopment analysis, as a branch of computational intelligence methods, has proved to be a reliable tool for innovation efficiency evaluation. Therefore, this paper aimed to apply DEA for the assessment of the European Union’s innovation efficiency from 2000 to 2020, when innovation was measured by patent, trademark, and design applications. The findings showed that the general EU innovation efficiency situation has improved over time, meaning that each programming period was more successful than the previous one. On the other hand, visible disparities were found across the member states, showing that Luxembourg is an absolute innovation efficiency leader, while Greece and Portugal achieved the lowest average efficiency scores. Both the application of the DEA method and the gathered results may act as viable guidelines on how to improve R&I policies and select future investment directions.

Keywords: research and innovation; innovation efficiency; computational intelligence; data envelopment analysis (DEA); European Union; R&I policy (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2023
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