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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)

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