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.
- MGMT Marketing and Consumption
- Recommender system
- tourist decision making process
- consumer information processing
- classifier systems
- open data analysis
Pantano, E., Priporas, C-V., Stylos, N., & Dennis, C. (2019). Facilitating tourists' decision making through open data analyses: A novel recommender system. Tourism Management Perspectives, 31, 323-331. https://doi.org/10.1016/j.tmp.2019.06.003