Profiling nascent entrepreneurs in Croatia - neural network approach
A significant body of research has been conducted to identify the most important characteristics of nascent entrepreneurs. The aim of this paper is to create a model for recognizing nascent entrepreneurs in Croatia, using the Global Entrepreneurship Monitor (GEM) data for 2014. In this research, the...
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Faculty of Economics in Osijek
2019-01-01
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Online Access: | https://hrcak.srce.hr/file/336575 |
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doaj-11f8961f16c24dc196dd8321de4250ab2020-11-25T01:49:18Zeng Faculty of Economics in OsijekEkonomski Vjesnik0353-359X1847-22062019-01-01322335346Profiling nascent entrepreneurs in Croatia - neural network approachPetra Mezulić Juric0Adela Has1Tihana Koprivnjak2Josip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, CroatiaJosip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, CroatiaJosip Juraj Strossmayer University of Osijek, Faculty of Economics in Osijek, Osijek, CroatiaA significant body of research has been conducted to identify the most important characteristics of nascent entrepreneurs. The aim of this paper is to create a model for recognizing nascent entrepreneurs in Croatia, using the Global Entrepreneurship Monitor (GEM) data for 2014. In this research, the artificial neural networks were used as a machine learning method which enabled the recognition of nascent entrepreneurs, as well as the selection of most important variables and profiling. The suggested model includes variables that describe examinees’ attitudes, skills and demographic characteristics, while the binary output variable identifies a nascent entrepreneur. In addition to testing the accuracy of the suggested model, the contribution of this paper lies in the profiling of nascent entrepreneurs in Croatia. This model could be a valuable tool for the government and entrepreneurship support institutions in creating policies and programmes based on recognizing the most important features of nascent entrepreneurs in order to improve entrepreneurial ecosystems.https://hrcak.srce.hr/file/336575nascent entrepreneursGEMneural networkmodelling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Petra Mezulić Juric Adela Has Tihana Koprivnjak |
spellingShingle |
Petra Mezulić Juric Adela Has Tihana Koprivnjak Profiling nascent entrepreneurs in Croatia - neural network approach Ekonomski Vjesnik nascent entrepreneurs GEM neural network modelling |
author_facet |
Petra Mezulić Juric Adela Has Tihana Koprivnjak |
author_sort |
Petra Mezulić Juric |
title |
Profiling nascent entrepreneurs in Croatia - neural network approach |
title_short |
Profiling nascent entrepreneurs in Croatia - neural network approach |
title_full |
Profiling nascent entrepreneurs in Croatia - neural network approach |
title_fullStr |
Profiling nascent entrepreneurs in Croatia - neural network approach |
title_full_unstemmed |
Profiling nascent entrepreneurs in Croatia - neural network approach |
title_sort |
profiling nascent entrepreneurs in croatia - neural network approach |
publisher |
Faculty of Economics in Osijek |
series |
Ekonomski Vjesnik |
issn |
0353-359X 1847-2206 |
publishDate |
2019-01-01 |
description |
A significant body of research has been conducted to identify the most important characteristics of nascent entrepreneurs. The aim of this paper is to create a model for recognizing nascent entrepreneurs in Croatia, using the Global Entrepreneurship Monitor (GEM) data for 2014. In this research, the artificial neural networks were used as a machine learning method which enabled the recognition of nascent entrepreneurs, as well as the selection of most important variables and profiling. The suggested model includes variables that describe examinees’ attitudes, skills and demographic characteristics, while the binary output variable identifies a nascent entrepreneur. In addition to testing the accuracy of the suggested model, the contribution of this paper lies in the profiling of nascent entrepreneurs in Croatia. This model could be a valuable tool for the government and entrepreneurship support institutions in creating policies and programmes based on recognizing the most important features of nascent entrepreneurs in order to improve entrepreneurial ecosystems. |
topic |
nascent entrepreneurs GEM neural network modelling |
url |
https://hrcak.srce.hr/file/336575 |
work_keys_str_mv |
AT petramezulicjuric profilingnascententrepreneursincroatianeuralnetworkapproach AT adelahas profilingnascententrepreneursincroatianeuralnetworkapproach AT tihanakoprivnjak profilingnascententrepreneursincroatianeuralnetworkapproach |
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