Understanding Clusters of Tourist Behavior Associations using Network Analysis

Identifying tourists' associated behaviors enables industry practitioners to design suitable and efficient marketing strategies for different tourist groups. This study proposes the use of the relationships between tourists and their behaviors for constructing networks, and the adoption of the community detection method for clustering tourist behavior networks. With this approach, tourists' behaviors can be clustered and visually investigated. Moreover, the evolution of groups of behaviors can be analyzed for obtaining insights into the origin of differences among different tourist groups. Survey data of visitors to Macao are used as a case study, and results provide valuable insights into tourists' behaviors.