The research intends to propose a data-driven approach to boost the tourist experience in integrated mobility services and discuss how the experience may be improved. In particular, the data-driven approach, owing to the design of a recommendation system based on a big-data analytics engine, makes it possible to: i) rank the tourist preferences for the most attractive Italian destinations on Google; ii) rank the main attractions – leisure, entertainment, culture, etc. – associated with single tourist destinations, obtained from the analysis of relevant thematic websites such as Tripadvisor, Minube, and Travel365. This study is dependent on the support of big social data for the concept of tourism experience co-design, with a focus on integrated mobility services. From a technological viewpoint, analytics on big social data is enabled by relying on a cloud-based data platform, such as Amazon web services (AWS), Microsoft Azure, or Google cloud platform (GCP). This has proved to be the key to regularly collecting, updating, and processing data from several heterogeneous sources such as Google search queries accessible via Google Trends, or any social data scraped from websites, as well as extracting relevant insights that can meet the business needs expressed by mobility companies.
ENHANCING TRAVELLER EXPERIENCE IN INTEGRATED MOBILITY SERVICES VIA BIG SOCIAL DATA ANALYTICS
Cuomo M. T.
Writing – Review & Editing
;Colosimo I.Membro del Collaboration Group
;Festa G.Validation
;La Rocca M.Conceptualization
2022-01-01
Abstract
The research intends to propose a data-driven approach to boost the tourist experience in integrated mobility services and discuss how the experience may be improved. In particular, the data-driven approach, owing to the design of a recommendation system based on a big-data analytics engine, makes it possible to: i) rank the tourist preferences for the most attractive Italian destinations on Google; ii) rank the main attractions – leisure, entertainment, culture, etc. – associated with single tourist destinations, obtained from the analysis of relevant thematic websites such as Tripadvisor, Minube, and Travel365. This study is dependent on the support of big social data for the concept of tourism experience co-design, with a focus on integrated mobility services. From a technological viewpoint, analytics on big social data is enabled by relying on a cloud-based data platform, such as Amazon web services (AWS), Microsoft Azure, or Google cloud platform (GCP). This has proved to be the key to regularly collecting, updating, and processing data from several heterogeneous sources such as Google search queries accessible via Google Trends, or any social data scraped from websites, as well as extracting relevant insights that can meet the business needs expressed by mobility companies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
