Issue |
E3S Web Conf.
Volume 295, 2021
International Scientific Forum on Sustainable Development and Innovation (WFSDI 2021)
|
|
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Article Number | 01051 | |
Number of page(s) | 12 | |
Section | Sustainable Development of Regions: Economic Aspect | |
DOI | https://doi.org/10.1051/e3sconf/202129501051 | |
Published online | 26 July 2021 |
Regional innovation systems efficiency analyses and evaluation: DEA approach implementation
Institute of Economics and Industrial Engineering SB RAS, 17 Academician Lavrentiev, Novosibirsk, Russia
* Corresponding author: konsult-i@yandex.ru
The innovative transformation is a necessary condition for sustainable economic development. The study reveals an assessment and comparative analysis of the Regional Innovation Systems’ (RIS) performance in the Russian Federation using Data Envelopment Analysis (DEA). The DEA model under the Variable Return to Scale (VRS) assumption, focused on output parameters, is used to estimate the relative technical efficiency of regions based on several input and output parameters. Based on the obtained results, a rating of regions was compiled: four groups of regions were identified depending on their technical efficiency level. It was revealed that the leading regions by innovative development level are assessed by the DEA somewhat differently. A comparative analysis of the innovation systems performance at the regional and federal levels allowed us to identify the most and least effective subjects of the Russian Federation, federal districts and economic regions. The main conclusion is that less than a third of the Russian regions use their production capabilities as efficient as possible, the remaining regions can significantly improve the way they use the available resources. The results of the study might be used in making managerial decisions at the country, federal districts and regions levels in order to develop measures and mechanisms for improving the efficiency of regional innovation systems.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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