Abstract
The 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.
Original language | English |
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Pages (from-to) | 430-438 |
Number of pages | 9 |
Journal | Tourism Management |
Volume | 60 |
Early online date | 17 Jan 2017 |
DOIs | |
Publication status | Published - Jun 2017 |
Research Groups and Themes
- Smart Networks for Sustainable Futures
- MGMT Marketing and Consumption
Keywords
- OPEN DATA
- Online reviews
- Tourism
- Travel propositions
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Dr Eleonora Pantano
- School of Management - Business School - Associate Professor in Retail and Marketing Technology
Person: Academic
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Dr Nikolaos Stylos
- School of Management - Business School - Associate Professor in Marketing and Digital Innovation
- Cabot Institute for the Environment
Person: Academic , Member