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dc.contributor.authorPantano, Eleonora
dc.contributor.authorPriporas, Constantinos-Vasilios
dc.contributor.authorStylos, Nikolaos
dc.date.accessioned2017-02-02T14:55:38Z
dc.date.available2017-02-02T14:55:38Z
dc.date.issued2017-01-17
dc.identifier.citationPantano, E., Priporas, C-V., & Stylos, N. (2017) '‘You will like it!’ using open data to predict tourists' response to a tourist attraction', Tourism Management, 60 (1), pp. 430-438.
dc.identifier.issn0261-5177
dc.identifier.doi10.1016/j.tourman.2016.12.020
dc.identifier.urihttp://hdl.handle.net/2436/620367
dc.description.abstractThe increasing amount of user-generated content spread via social networking services such as reviews, comments, and past experiences, has made a great deal of information available. Tourists can access this information to support their decision making process. This information is freely accessible online and generates so-called “open data”. While many studies have investigated the effect of online reviews on tourists’ decisions, none have directly investigated the extent to which open data analyses might predict tourists’ response to a certain destination. To this end, our study contributes to the process of predicting tourists’ future preferences via MathematicaTM, , software that analyzes a large set of the open data (i.e. tourists reviews) that is freely available on Tripadvisor. This is devised by generating the classification function and the best model for predicting the destination tourists would potentially select. The implications for the tourist industry are discussed in terms of research and practice.
dc.language.isoen
dc.publisherElsevier
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0261517716302680
dc.subjectopen data
dc.subjectonline reviews
dc.subjecttourism
dc.subjecttravel propositions
dc.title‘You will like it!’ using open data to predict tourists' response to a tourist attraction
dc.typeJournal article
dc.identifier.journalTourism Management
dc.date.accepted2016-12-29
rioxxterms.funderUniversity of Wolverhampton
rioxxterms.identifier.projectUoW020217NS
rioxxterms.versionAM
rioxxterms.licenseref.urihttps://creativecommons.org/CC BY-NC-ND 4.0
rioxxterms.licenseref.startdate2017-02-02
dc.source.volume60
dc.source.issue1
dc.source.beginpage430
dc.source.endpage438
refterms.dateFCD2018-10-18T15:44:38Z
refterms.versionFCDAM
refterms.dateFOA2017-01-01T00:00:00Z
html.description.abstractThe increasing amount of user-generated content spread via social networking services such as reviews, comments, and past experiences, has made a great deal of information available. Tourists can access this information to support their decision making process. This information is freely accessible online and generates so-called “open data”. While many studies have investigated the effect of online reviews on tourists’ decisions, none have directly investigated the extent to which open data analyses might predict tourists’ response to a certain destination. To this end, our study contributes to the process of predicting tourists’ future preferences via MathematicaTM, , software that analyzes a large set of the open data (i.e. tourists reviews) that is freely available on Tripadvisor. This is devised by generating the classification function and the best model for predicting the destination tourists would potentially select. The implications for the tourist industry are discussed in terms of research and practice.


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