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BAYESIAN APPROACH TO THE PROCESS OF IDENTIFICATION OF THE DETERMINANTS OF INNOVATIVENESS

100%
Czyżewska M., Mroczek T.
Finansowy Kwartalnik Internetowy e-Finanse
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2014
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vol. 10
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issue 2
44-56
EN
Bayesian belief networks are applied in determining the most important factors of the innovativeness level of national economies. The paper is divided into two parts. The first presentsthe basic theory of Bayesian networks whereas in the second, the belief networks have been generated by an inhouse developed computer system called BeliefSEEKER which was implemented to generate the determinants influencing the innovativeness level of national economies.Qualitative analysis of the generated belief networks provided a way to define a set of the most important dimensions influencing the innovativeness level of economies and then the indicators that form these dimensions. It has been proven that Bayesian networks are very effective methods for multidimensional analysis and forming conclusions and recommendations regarding the strength of each innovative determinant influencing the overall performance of a country’s economy.
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Assessment of Young People’s Attitudes Towards Sustainable Entrepreneurship with Machine Learning Techniques Use

81%
Mroczek T., Kaszuba-Perz A., Czyżewska M.
Horyzonty Polityki
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2022
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vol. 13
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issue 42
187-202
EN
RESEARCH OBJECTIVE: The main purpose of the research is to assess whether the young generation in Poland has the potential to build sustainable companies by evaluating the attitudes of university students towards sustainable entrepreneurship.. THE RESEARCH PROBLEM AND METHODS: The readiness to create a sustainable enterprise was assessed on the basis of self-assessment of pro-social attitudes, business intentions and knowledge of social and environmental aspects in business with the use of multidimensional analysis based on machine learning methods. THE PROCESS OF ARGUMENTATION: A significant challenge for policymakers, scientists and entrepreneurs is solving important social and environmental problems through the development of sustainable entrepreneurship. The implementation of this concept requires efforts to educate and shape pro-social attitudes, especially among the young generation. Therefore, the research focuses on identifying and assessing the attitudes and awareness level of pro-social aspects in business and recognition of entrepreneurial intentions among representatives of this generation. RESEARCH RESULTS: The research results show that young people have an intuitive sense of what sustainable business is all about, but the formal knowledge in this area is low. Financial aspects, i.e. the possibility of obtaining significant income from own business, as well as independence and the possibility of being a manager, turned out to be much more motivating for entrepreneurship than the possibility of changing the world for the better, helping local communities or protecting the environment. CONCLUSIONS, INNOVATIONS AND RECOMMENDATIONS: The innovative approach to multidimensional data analysis highlighted the lack of knowledge and insufficient level of pro-social attitudes among the young generation, which is a particularly worrying phenomenon in the context of formulated challenges and social and environmental needs.
3
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Zastosowanie metod uczenia maszynowego w badaniu czynników wzrostu przedsiębiorczości

81%
Czyżewska M., Mroczek T., Lewicki A., Cwynar A.
Prace Komisji Geografii Przemysłu Polskiego Towarzystwa Geograficznego
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2017
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vol. Volume 31, Issue 4
169-186
PL
Przedsiębiorczość ma kluczowe znaczenie zarówno dla wzrostu gospodarczego, jak i rozumianego wielowymiarowo rozwoju, co znalazło odzwierciedlenie w przyjmowaniu jej za jeden z czynników produkcji przez niektóre teorie. Zarówno teoretyczne, jak i empiryczne badania przedsiębiorczości świadczą o tym, że jest ona kształtowana przez wiele różnorodnych czynników, będąc wyjątkowo złożonym zjawiskiem. Tradycyjne metody badawcze okazują się niewystarczające wobec wspomnianej złożoności zjawiska. Niniejszy artykuł prezentuje wyniki badania dotyczącego wpływu poszczególnych wskaźników opracowanych przez Bank Światowy w World Governance Indicators na wzrost przedsiębiorczości. Celem artykułu jest empiryczna weryfikacja przydatności metod uczenia maszynowego w selekcji czynników kluczowych dla przedsiębiorczości w sytuacji, gdy dokonuje się jej z wykorzystaniem dużych zbiorów wielowymiarowych i zmiennych danych. Zastosowana metoda wykazała istotne różnice pomiędzy kluczowymi czynnikami determinującymi wzrost przedsiębiorczości w pięciu grupach krajów, wydzielonych ze względu na wartość tego wzrostu mierzoną przyrostem nowo zakładanych przedsiębiorstw. Otrzymane wyniki świadczą o tym, że do badania istoty i determinant przedsiębiorczości mogą zostać zaprzęgnięte niestandardowe metody, rzucając nowe światło na to zjawisko.
EN
Entrepreneurship is crucial both for economic growth and development which is reflected in the adoption of entrepreneurship as the factor of production in certain theories. Both theoretical and empirical research present entrepreneurship as a complex phenomenon shaped by a range of different factors. Traditional research methods are insufficient with respect to the complexity of the phenomenon. This article presents the results of research on the impact of the indicators developed by the World Bank in World Governance Indicators on the entrepreneurship growth. The aim of the article is the empirical verification of machine learning use in the selection of key factors for entrepreneurship in situations when applying large multidimensional and variable data. The applied method revealed significant differences between the key factors determining the growth of entrepreneurship in five groups of countries, categorized by the value of this growth measured by the growth in newly established enterprises. The results indicate that the applying unconventional methods to research on entrepreneurship determinants shed new light on this phenomenon.
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