Factors influencing the co-occurrence of visits to attractions: the case of Madrid, Spain

Abstract

Large destinations such as cities usually offer multiple and diverse attractions, a selection of which will be visited by tourists during their stay. This study analyses the factors influencing the probability of the co-occurrence of visits to attractions in the city of Madrid (Spain). On the basis of five years (2013–2018) of user-generated data, we built a network formed by the attractions visited by the tourists and fitted it to an exponential random graph model. The results show that a tourist's decision to visit a particular attraction was influenced by its popularity and rating. In addition, homophily in popularity, rating and some attraction categories was detected. In the analysis made of the temporal trend of the attraction network, it was found that homophily in the category of museums and theatres strengthened over the study period. Identifying the forces that connect attractions is crucial for their efficient management, promotion, and preservation.