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Mapping Financial Performances in Italian ICT-Related Firms via Self-organizing Maps

In: Network, Smart and Open

Author

Listed:
  • Marina Resta

    (University of Genova)

  • Roberto Garelli

    (University of Genova)

  • Renata Paola Dameri

    (University of Genova)

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.

Suggested Citation

  • Marina Resta & Roberto Garelli & Renata Paola Dameri, 2018. "Mapping Financial Performances in Italian ICT-Related Firms via Self-organizing Maps," Lecture Notes in Information Systems and Organization, in: Rita Lamboglia & Andrea Cardoni & Renata Paola Dameri & Daniela Mancini (ed.), Network, Smart and Open, pages 271-281, Springer.
    • Handle: RePEc:spr:lnichp:978-3-319-62636-9_18
    DOI: 10.1007/978-3-319-62636-9_18
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