Identifying macroscopic features in foreign visitor travel pathways

TL;DR

This study uses higher-order network analysis to identify characteristic travel pathways of foreign visitors in Japan, providing more detailed insights into travel patterns than traditional pairwise network methods.

Contribution

It introduces a higher-order network framework to analyze travel pathways, offering a novel approach for understanding complex visitor movement patterns.

Findings

Identification of common travel pathways among foreign visitors

Enhanced understanding of multi-destination travel behavior

Potential applications in tourism marketing strategies

Abstract

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.