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

Eleonora Pantano, Constantinos-Vasilios Priporas, Nikolaos Stylos*, Charles Dennis

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)
271 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)323-331
Number of pages9
JournalTourism Management Perspectives
Early online date2 Jul 2019
Publication statusE-pub ahead of print - 2 Jul 2019

Structured keywords

  • MGMT Marketing and Consumption


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


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