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Original scientific paper

COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS

Marijana Zekić-Sušac ; Faculty of Economics, University of J.J. Strossmayer in Osijek, Osijek, Croatia
Nataša Šarlija   ORCID icon orcid.org/0000-0003-2600-9735 ; Faculty of Economics, University of J.J. Strossmayer in Osijek, Osijek, Croatia
Sanja Pfeifer   ORCID icon orcid.org/0000-0002-7394-3080 ; Faculty of Economics, University of J.J. Strossmayer in Osijek, Osijek, Croatia

Fulltext: english, pdf (161 KB) pages 306-317 downloads: 6.159* cite
APA 6th Edition
Zekić-Sušac, M., Šarlija, N. & Pfeifer, S. (2013). COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS. Croatian Operational Research Review, 4 (1), 306-317. Retrieved from https://hrcak.srce.hr/97407
MLA 8th Edition
Zekić-Sušac, Marijana, et al. "COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS." Croatian Operational Research Review, vol. 4, no. 1, 2013, pp. 306-317. https://hrcak.srce.hr/97407. Accessed 12 Jul. 2020.
Chicago 17th Edition
Zekić-Sušac, Marijana, Nataša Šarlija and Sanja Pfeifer. "COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS." Croatian Operational Research Review 4, no. 1 (2013): 306-317. https://hrcak.srce.hr/97407
Harvard
Zekić-Sušac, M., Šarlija, N., and Pfeifer, S. (2013). 'COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS', Croatian Operational Research Review, 4(1), pp. 306-317. Available at: https://hrcak.srce.hr/97407 (Accessed 12 July 2020)
Vancouver
Zekić-Sušac M, Šarlija N, Pfeifer S. COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS. Croatian Operational Research Review [Internet]. 2013 [cited 2020 July 12];4(1):306-317. Available from: https://hrcak.srce.hr/97407
IEEE
M. Zekić-Sušac, N. Šarlija and S. Pfeifer, "COMBINING PCA ANALYSIS AND ARTIFICIAL NEURAL NETWORKS IN MODELLING ENTREPRENEURIAL INTENTIONS OF STUDENTS", Croatian Operational Research Review, vol.4, no. 1, pp. 306-317, 2013. [Online]. Available: https://hrcak.srce.hr/97407. [Accessed: 12 July 2020]

Abstracts
Despite increased interest in the entrepreneurial intentions and career choices of young adults, reliable prediction models are yet to be developed. Two nonparametric methods were used in this paper to
model entrepreneurial intentions: principal component analysis (PCA) and artificial neural networks (ANNs). PCA was used to perform feature extraction in the first stage of modelling, while artificial neural networks were used to classify students according to their entrepreneurial intentions in the second stage. Four modelling strategies were tested in order to find the most efficient model. Dataset
was collected in an international survey on entrepreneurship self-efficacy and identity. Variables describe students’ demographics, education, attitudes, social and cultural norms, self-efficacy and
other characteristics. The research reveals benefits from the combination of the PCA and ANNs in modeling entrepreneurial intentions, and provides some ideas for further research.

Keywords
Classification; Entrepreneurial intentions; Modelling; Artificial neural networks; Principal component analysis

Hrčak ID: 97407

URI
https://hrcak.srce.hr/97407

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