Abstract
In this work, we explore the application of machine learning models (MLM) to the analysis of firms’ performance. To such aim, we consider a bunch of financial indicators on firms operating in the Information and Communication Technology (ICT) sector, with attention to enterprises providing ICT related-services. The rationale is to highlight the potential of MLM to exploit the complexity of financial data, and to offer a handy way to visualize the related information. In fact, instead of performing classical analysis, we discuss how to apply to those indicators Self-Organizing Maps-SOMs—that are well suited to manage high dimensional and complex datasets to extract their relevant features. It emerges that SOMs are useful in clustering companies depending on multi-dimensional criteria and in analysing hidden relations in companies’ performances.
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Notes
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Analisi Informatizzata delle Aziende Italiane, Bureau Van Dijk, http://www.bvdinfo.com/it-it/home.
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See Fig. 3.
Situation of ICT related-services Italian firms, from an authors’ proprietary elaboration
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Resta, M., Garelli, R., Dameri, R.P. (2018). Mapping Financial Performances in Italian ICT-Related Firms via Self-organizing Maps. In: Lamboglia, R., Cardoni, A., Dameri, R., Mancini, D. (eds) Network, Smart and Open. Lecture Notes in Information Systems and Organisation, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-62636-9_18
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