In recent years, several initiatives have been taken by governments to support investments in small and medium-sized enterprises. The aim is to foster their access to finance, and thus enhance their competitiveness. This paper investigates, through artificial intelligence, the socio-economic effects of these financial instruments on the performance and business continuity of the beneficiary companies. Moreover, this paper illustrates how artificial intelligence can support public decision-makers in creating and deploying regional policies. This study is a part of the collaboration among Arisk Srl and some policy-makers of the Regional Government of Piedmont (Italy).

Using machine learning to assess public policies: a real case study for supporting SMEs development in Italy / Perboli, Guido; Tronzano, Andrea; Rosano, Mariangela; Tarantino, Luciano; Velardocchia, Filippo. - ELETTRONICO. - (2021), pp. 1-6. (Intervento presentato al convegno 2021 IEEE Technology & Engineering Management Conference - Europe (TEMSCON-EUR) tenutosi a Virtual nel 17-20 May 2021) [10.1109/TEMSCON-EUR52034.2021.9488581].

Using machine learning to assess public policies: a real case study for supporting SMEs development in Italy

Perboli, Guido;Rosano, Mariangela;Velardocchia, Filippo
2021

Abstract

In recent years, several initiatives have been taken by governments to support investments in small and medium-sized enterprises. The aim is to foster their access to finance, and thus enhance their competitiveness. This paper investigates, through artificial intelligence, the socio-economic effects of these financial instruments on the performance and business continuity of the beneficiary companies. Moreover, this paper illustrates how artificial intelligence can support public decision-makers in creating and deploying regional policies. This study is a part of the collaboration among Arisk Srl and some policy-makers of the Regional Government of Piedmont (Italy).
2021
978-1-6654-4091-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2916926