Identifying macroscopic features in foreign visitor travel pathways
Tatsuro Kawamoto () and
Ryutaro Hashimoto ()
Additional contact information
Tatsuro Kawamoto: National Institute of Advanced Industrial Science and Technology
Ryutaro Hashimoto: Waseda University
The Japanese Economic Review, 2021, vol. 72, issue 1, No 6, 129-144
Abstract:
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.
Keywords: Mobility patterns; Community detection; Higher-order networks (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s42973-020-00058-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:jecrev:v:72:y:2021:i:1:d:10.1007_s42973-020-00058-4
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/42973
DOI: 10.1007/s42973-020-00058-4
Access Statistics for this article
The Japanese Economic Review is currently edited by Michihiro Kandori
More articles in The Japanese Economic Review from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().