The aim of this research is to propose and discuss how a data-driven approach (Cuomo et al., 2020) may improve and enhance the tourist experience in integrated door-to-door mobility services (Schulz et al., 2020). In particular, the data driven approach, thanks 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 in 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.
Enhancing Tourist Experience in Integrated Door-To-Door Mobility Services on Big Social Data Analytics
Maria Teresa Cuomo
;Ivan Colosimo;Giuseppe Festa;Michele La Rocca
2021-01-01
Abstract
The aim of this research is to propose and discuss how a data-driven approach (Cuomo et al., 2020) may improve and enhance the tourist experience in integrated door-to-door mobility services (Schulz et al., 2020). In particular, the data driven approach, thanks 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 in 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
