European Union Innovation Efficiency Assessment Based on Data Envelopment Analysis

Author:

Andrijauskiene Meda1ORCID,Ioannidis Dimosthenis2ORCID,Dumciuviene Daiva1ORCID,Dimara Asimina23ORCID,Bezas Napoleon2ORCID,Papaioannou Alexios2,Krinidis Stelios2

Affiliation:

1. School of Economics and Business, Kaunas University of Technology, LT-44029 Kaunas, Lithuania

2. Centre for Research and Technology (CERTH)—Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece

3. Intelligent Systems Lab, Department of Cultural Technology and Communication, University of the Aegean, 81100 Mytilene, Greece

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.

Funder

European Social Fund

Publisher

MDPI AG

Subject

Economics, Econometrics and Finance (miscellaneous),Development

Reference59 articles.

1. Anderson, Henry Junior, and Stejskal, Jan (2019). Diffusion efficiency of innovation among EU member states: A data envelopment analysis. Economies, 7.

2. Andrijauskiene, Meda, Dumciuviene, Daiva, and Vasauskaite, Jovita (2021). Redeveloping the national innovative capacity framework: European Union perspective. Economies, 9.

3. Innovation and Economic Growth: An empirical investigation of European countries;Apostolos;Applied Economics Letter,2017

4. Global innovation efficiency assessment of EU member and candidate countries via DEA-EATWIOS multi-criteria methodology;Aytekin;Technology in Society,2022

5. Bacon, David, Forner, Dominik, and Ozcan, Sercan (2019). 8th International Conference on Data Science, Technology and Applications, SciTePress.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3