  Human travel patterns are commonly studied as networks in which the points of
departure and destination are encoded as nodes and the travel frequency between
two points is recorded as a weighted edge. However, because travelers often
visit multiple destinations, which constitute pathways, an analysis
incorporating pathway statistics is expected to be more informative over an
approach based solely on pairwise frequencies. Hence, in this study, we apply a
higher-order network representation framework to identify characteristic travel
patterns from foreign visitor pathways in Japan. We expect that the results
herein are mainly useful for marketing research in the tourism industry.
