Autori
Garelli, Roberto
Dameri, Renata Paola
Resta, Marina

Titolo
Data analytics e intelligenza artificiale per l'analisi di bilancio. Performance e profili di business degli spin-off accademici
Periodico
ImpresaProgetto
Anno: 2017 - Volume: 2017 - Fascicolo: 3 - Pagina iniziale: 1 - Pagina finale: 27

This research applies neural networks – namely: Self-Organising Maps (SOMs) - to analyse a bunch of financial indicators drawn from the balance sheet of academic spin-offs. The goal of the work is twofold: first, it aims at processing financial data to extract knowledge about the still uncertain role and strategic profile of academic spin-offs; second, it aims at understating whether SOMs are able to support investigations on firms’ performance, and to decide strategic orientation thanks to the processing of financial indicators. After a deep literature review about both the application of SOMs to financial reporting data and the business profile of academic spin-offs, the paper carries on an empirical investigation on 810 Italian academic spin-offs, using their financial reporting data. The results show that SOMs succeed in extracting the main features of different academic spin-off archetypes that can be then explained via traditional financial analysis instruments.



SICI: 1824-3576(2017)2017:3<1:DAEIAP>2.0.ZU;2-4
Testo completo: https://www.impresaprogetto.it/sites/impresaprogetto.it/files/articles/dameri_dataanalytics_3_12bis_0.pdf

Esportazione dati in Refworks (solo per utenti abilitati)

Biblioteche ACNP che possiedono il periodico