Cluster Analysis in Tourism

Cluster analysis is a family of multivariate techniques used for identifying homogenous groups of objects or individuals based on their similarities or dissimilarities in a set of measured variables. Clustering methods are also considered to be within the main unsupervised machine learning techniques.

One of the most common applications of cluster analysis in tourism research is market segmentation. The technique attempts to identify homogenous subsets of tourists to better understand their preferences and needs, and to modify and adapt marketing efforts to specific segments, thus allowing more efficient resource allocation. The variables could be demographic, trip-related, motivations, expectations, and the like. This method is also known as a posteriori or data-driven segmentation.

A specific application to tourism is often seen in the study of social impacts, particularly to understand the host communities’ perceptions of this phenomenon. Based on survey data, researchers may be...