This paper presents the development of an integrated data system tailored for the Italian regions, combining microdata from the Bank of Italy’s and ISTAT’s surveys. These datasets offer an in-depth analysis of both domestic and international aspects of tourism, framed within the theoretical context of the tourism determinants. By merging this integrated dataset with additional data from other statistical sources, this study offers a queryable relational database enabling granular regional analysis. Currently, tourism statistics in Italy are fragmented and do not provide a unified picture of tourism in its many aspects. The relational model’s interoperability addresses Italy’s fragmented tourism data landscape, and its data definition language represents an important step towards the creation of a unified tourism archive. Micro-data allows for different statistical analyses than those usually carried out with aggregated data, increasing knowledge of the dynamics of the sector.

Development of an integrated data system for regional tourism analysis in Italy: A microdata perspective

Samuele Cesarini;Fabrizio Antolini;Ivan Terraglia
2025-01-01

Abstract

This paper presents the development of an integrated data system tailored for the Italian regions, combining microdata from the Bank of Italy’s and ISTAT’s surveys. These datasets offer an in-depth analysis of both domestic and international aspects of tourism, framed within the theoretical context of the tourism determinants. By merging this integrated dataset with additional data from other statistical sources, this study offers a queryable relational database enabling granular regional analysis. Currently, tourism statistics in Italy are fragmented and do not provide a unified picture of tourism in its many aspects. The relational model’s interoperability addresses Italy’s fragmented tourism data landscape, and its data definition language represents an important step towards the creation of a unified tourism archive. Micro-data allows for different statistical analyses than those usually carried out with aggregated data, increasing knowledge of the dynamics of the sector.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11575/161620
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