If the COVID-19 pandemic disrupted the Italian performing arts industry, the European Union and the Italian Government were ready to make up for the lack of resources of cultural organizations. Digitalization was at the heart of European and State policies and funding and provided grants to organizations that demonstrated spending on marketing and IT, digitalization of businesses and communication. This paper aims to understand how the COVID-19 pandemic forced a sample of 992 Italian performing arts to cope with stringency and resulted as a stimulus to develop digitalization, which remained a precious legacy in the post-pandemic 2022. A k-means clustering will be implemented to show that the sample can be separated into three clusters for ratios of 2022’s program service revenues, public grants, the marketing and IT expense and the personnel one. Our findings show that the highest public grants can be found in the least crowded cluster with the lowest program service revenue, while the highest program service revenues are combined with marketing and IT expense as one third of expenses in the most crowded cluster. The lowest personnel expense is connected to the highest marketing and IT expenses. Public funds remain granted for digitalization of business and communication.

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Digitalization and Economic Performance of Italian Performing Arts in 2022

  • Angela Besana,
  • Antonella Sau

摘要

If the COVID-19 pandemic disrupted the Italian performing arts industry, the European Union and the Italian Government were ready to make up for the lack of resources of cultural organizations. Digitalization was at the heart of European and State policies and funding and provided grants to organizations that demonstrated spending on marketing and IT, digitalization of businesses and communication. This paper aims to understand how the COVID-19 pandemic forced a sample of 992 Italian performing arts to cope with stringency and resulted as a stimulus to develop digitalization, which remained a precious legacy in the post-pandemic 2022. A k-means clustering will be implemented to show that the sample can be separated into three clusters for ratios of 2022’s program service revenues, public grants, the marketing and IT expense and the personnel one. Our findings show that the highest public grants can be found in the least crowded cluster with the lowest program service revenue, while the highest program service revenues are combined with marketing and IT expense as one third of expenses in the most crowded cluster. The lowest personnel expense is connected to the highest marketing and IT expenses. Public funds remain granted for digitalization of business and communication.