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Title | Implementation of knowledge economy and innovation through business education |
Authors |
Habenko, M.
Koibichuk, Vitaliia Vasylivna Krawczyk, D. Mayboroda, Tetyana Samoilikova, Anastasiia Viktorivna |
ORCID |
http://orcid.org/0000-0002-3540-7922 http://orcid.org/0000-0002-4547-5822 http://orcid.org/0000-0001-8639-5282 |
Keywords |
бізнес-освітня конкуренція business-education coopetition зайнятість employment підприємництво entrepreneurship вища освіта higher education трансфер інновацій innovation transfer економіка знань knowledge economy нове підприємство new enterprise |
Type | Article |
Date of Issue | 2023 |
URI | https://essuir.sumdu.edu.ua/handle/123456789/93963 |
Publisher | Academic Research and Publishing UG |
License | Creative Commons Attribution 4.0 International License |
Citation | Habenko, M., Koibichuk, V., Krawczyk, D., Mayboroda, T., Samoilikova, A. (2023). Implementation of knowledge economy and innovation through business education. SocioEconomic Challenges, 7(4), 215-226. https://doi.org/10.61093/sec.7(4).215-226.2023. |
Abstract |
The article’s purpose is to analyse the issue of implementation of knowledge economy and innovation through business education based on cluster analysis. The role of knowledge economy, innovation transfer, entrepreneurship and business-education coopetition are grounded to achieve economic growth and sustainable development. Input data withing the distribution of the knowledge economy through business education include a data of 23 countries for the following indicators: new registered enterprises, labour force, employment in industry, proportion of population studying ‘Business, Administration and Law’, proportion of population studying ‘Services’ and proportion of population studying ‘Economics’. Using data normalization, Ward and Sturges methods and Statgraphics Centurion 19 soft five clusters were determined to show hidden dependencies and structure in countries sample in this research context. The first cluster includes 2 countries (Austria and the United Kingdom), the second – 11 countries (Belgium, Portugal, Denmark, Italy, Lithuania, Latvia, Poland, Ukraine, Croatia, Norway, and the Netherlands), the third – 5 countries (Bulgaria, Spain, France, Switzerland, and Finland), the fourth – 3 countries (Estonia, Germany and Sweden), and the fifth – 2 countries (the Czech Republic and Hungary). Due to building dendrogram of distribution on clusters and graph of agglomeration distance the quality of countries distribution into clusters was confirmed. Obtained results can be useful for further research and improving the state innovation, information and educational policy based on positive experience of neighbour countries within certain formed cluster |
Appears in Collections: |
SocioEconomic Challenges (SEC) |
Views
Argentina
1
Belgium
1
Japan
1
Singapore
1
Ukraine
22
United Kingdom
1
United States
142
Unknown Country
171
Downloads
Japan
1
Singapore
1
United States
139
Unknown Country
1
Files
File | Size | Format | Downloads |
---|---|---|---|
Habenko_SEC_4_2023_17.pdf | 1.07 MB | Adobe PDF | 142 |
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