What is the “Personality” of a tourism destination?

Researching online before booking a vacation can be seen as a common habit of customers nowadays. In this context, Recommender Systems (RSs) are aiming to support the customers to find the right products, but they face domain specific challenges since tourism products are typically very complex and related to emotional experiences. To counteract these challenges, comprehensive user models for capturing the preferences and personality of travellers have been introduced. One of these models is the so-called Seven-Factor Model. This paper introduces an automated way for determining the Seven-Factor representation of tourism destinations to enable a matchmaking for RSs. In particular, exploratory data analysis, cluster analysis, and regression analysis are conducted not only to find a mapping of destinations onto the Seven-Factors, but also to foster a better understanding of the relationship between destination attributes and the Seven-Factors. This work provides clear evidence that a tourism destination’s Seven-Factor representation can be determined by taking its attributes into account. This is an extended version of a conference paper entitled “Mapping of tourism destinations to travel behavioural patterns” previously published in the proceedings of Information and Communication Technologies in Tourism 2018 Conference (ENTER 2018) held in Jonkoping, Sweden, January 24–26, 2018.