The Properties of Tourist Destination Networks: Based on Hotel Reservation Data

This study examines key properties of tourist destination networks. We constructed a network data set using a large collection of tourist trip data that contains 217,686 distinct trips taken by 200,153 tourists across 39,901 cities in 195 countries. Using the data set, we mapped and simulated the tourist destination networks using three canonical network models. We found that the tourist destination networks have long diameters, in contrast to many social and economic networks to which they belong, but conform to the high clustering and scale-free properties. We found that none of the three network models can adequately capture the formation mechanisms of the tourist destination networks; the destination networks share certain, but not all, of the key properties of each of the three network models. Such inadequacy calls for developing new network models to examine the connections and topologies of tourist destinations that are grounded on tourists’ decision making.