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Facilitating tourists' decision making through open data analyses: A novel recommender system

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)323-331
Number of pages9
JournalTourism Management Perspectives
Early online date2 Jul 2019
DateAccepted/In press - 15 Apr 2019
DateE-pub ahead of print (current) - 2 Jul 2019


A number of studies have recently been published reporting researchers’ efforts to create new, more efficient recommender systems to support tourists’ decision making. This current research operationalizes a recommender system by filtering user-generated data that is abundantly available online, based on individuals’ evaluation criteria, to produce a dataset for analysis. Drawing upon an array of predictive models, this research proposes a new recommender system able to facilitate the tourist decision making process through successful managing of open data. It further presents a rating estimation method using ratings that pertain to online users-specified criteria (profile). The model is able to predict consumers’ ratings of a certain product with high reliability starting from open data on their profiles.

    Research areas

  • Recommender system, tourist decision making process, consumer information processing, classifier systems, open data analysis

    Structured keywords

  • MGMT Marketing and Consumption



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    Rights statement: This is the accepted author manuscript (AAM). The final published version (version of record) is available online via Elsevier at . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 761 KB, PDF document

    Embargo ends: 2/07/20

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    Licence: CC BY-NC-ND


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