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Original scientific paper
https://doi.org/10.17535/crorr.2016.0016

Predicting company growth using logistic regression and neural networks

Marijana Zekić-Sušac ; Faculty of Economics in Osijek, University of Josip Juraj Strossmayer in Osijek, Gajev trg 7, 31000 Osijek, Croatia
Nataša Šarlija   ORCID icon orcid.org/0000-0003-2600-9735 ; Faculty of Economics in Osijek, University of Josip Juraj Strossmayer in Osijek, Gajev trg 7, 31000 Osijek, Croatia
Adela Has ; Faculty of Economics in Osijek, University of Josip Juraj Strossmayer in Osijek, Gajev trg 7, 31000 Osijek, Croatia
Ana Bilandžić ; Faculty of Economics in Osijek, University of Josip Juraj Strossmayer in Osijek, Gajev trg 7, 31000 Osijek, Croatia

Fulltext: english, pdf (256 KB) pages 229-248 downloads: 2.142* cite
APA 6th Edition
Zekić-Sušac, M., Šarlija, N., Has, A. & Bilandžić, A. (2016). Predicting company growth using logistic regression and neural networks. Croatian Operational Research Review, 7 (2), 229-248. https://doi.org/10.17535/crorr.2016.0016
MLA 8th Edition
Zekić-Sušac, Marijana, et al. "Predicting company growth using logistic regression and neural networks." Croatian Operational Research Review, vol. 7, no. 2, 2016, pp. 229-248. https://doi.org/10.17535/crorr.2016.0016. Accessed 18 Oct. 2019.
Chicago 17th Edition
Zekić-Sušac, Marijana, Nataša Šarlija, Adela Has and Ana Bilandžić. "Predicting company growth using logistic regression and neural networks." Croatian Operational Research Review 7, no. 2 (2016): 229-248. https://doi.org/10.17535/crorr.2016.0016
Harvard
Zekić-Sušac, M., et al. (2016). 'Predicting company growth using logistic regression and neural networks', Croatian Operational Research Review, 7(2), pp. 229-248. https://doi.org/10.17535/crorr.2016.0016
Vancouver
Zekić-Sušac M, Šarlija N, Has A, Bilandžić A. Predicting company growth using logistic regression and neural networks. Croatian Operational Research Review [Internet]. 2016 [cited 2019 October 18];7(2):229-248. https://doi.org/10.17535/crorr.2016.0016
IEEE
M. Zekić-Sušac, N. Šarlija, A. Has and A. Bilandžić, "Predicting company growth using logistic regression and neural networks", Croatian Operational Research Review, vol.7, no. 2, pp. 229-248, 2016. [Online]. https://doi.org/10.17535/crorr.2016.0016

Abstracts
The paper aims to establish an efficient model for predicting company growth by leveraging the strengths of logistic regression and neural networks. A real dataset of Croatian companies was used which described the relevant industry sector, financial ratios, income, and assets in the input space, with a dependent binomial variable indicating whether a company had high-growth if it had annualized growth in assets by more than 20% a year over a three-year period. Due to a large number of input variables, factor analysis was performed in the pre -processing stage in order to extract the most important input components. Building an efficient model with a high classification rate and explanatory ability required application of two data mining methods: logistic regression as a parametric and neural networks as a non -parametric method. The methods were tested on the models with and without variable reduction. The classification accuracy of the models was compared using statistical tests and ROC curves. The results showed that neural networks produce a significantly higher classification accuracy in the model when incorporating all available variables. The paper further discusses the advantages and disadvantages of both approaches, i.e. logistic regression and neural networks in modelling company growth. The suggested model is potentially of benefit to investors and economic policy makers as it provides support for recognizing companies with growth potential, especially during times of economic downturn.

Keywords
company growth; factor analysis; logistic regression; neural networks; prediction model

Hrčak ID: 174204

URI
https://hrcak.srce.hr/174204

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