With the rapid development of Internet and social media, a massive amount of data is generated, recorded, gathered and stored, heralding the beginning of a new era of Big Data. The concept refers to the sources, variety, velocity, and volumes of the data available. The accelerating use of Big Data has also brought fundamental changes in tourism sectors, offering new opportunities. In particular, public data published on microblogging social platforms, like Twitter, can be exploited to improve the management of tourism destinations. Given the borderless nature of this new data, tourism statistics are on the frontline of Big Data-related innovations of statistical sources and methods. However, when considering the potential benefits of Big Data for the analysis of tourism, the many different types of variables which can be appropriately and effectively utilised need to be analysed. This study, using an inductive analysis of tweets collected in the touristic area of Catania (Sicily) and Cagliari (Sardinia) from 2010 to 2019, highlights the kind of tourism-related information that can be inferred from public online records on Twitter. Results show that Big Data can be useful for local stakeholders in decision-making processes and for planning tourism development strategies.

The role of Big Data in tourism destination management: some empirical evidence

Asero Vincenzo;
2020-01-01

Abstract

With the rapid development of Internet and social media, a massive amount of data is generated, recorded, gathered and stored, heralding the beginning of a new era of Big Data. The concept refers to the sources, variety, velocity, and volumes of the data available. The accelerating use of Big Data has also brought fundamental changes in tourism sectors, offering new opportunities. In particular, public data published on microblogging social platforms, like Twitter, can be exploited to improve the management of tourism destinations. Given the borderless nature of this new data, tourism statistics are on the frontline of Big Data-related innovations of statistical sources and methods. However, when considering the potential benefits of Big Data for the analysis of tourism, the many different types of variables which can be appropriately and effectively utilised need to be analysed. This study, using an inductive analysis of tweets collected in the touristic area of Catania (Sicily) and Cagliari (Sardinia) from 2010 to 2019, highlights the kind of tourism-related information that can be inferred from public online records on Twitter. Results show that Big Data can be useful for local stakeholders in decision-making processes and for planning tourism development strategies.
2020
978-2-9574541-0-5
Big Data, Tourism Destination Management, Twitter
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/487831
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