Pattern Recognition of Travel Mobility in a City Destination: Application of Network Motif Analytics

Sangwon Park, Ren Ridge Zhong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Urban tourism is considered a complex system. Tourists who visit cities have diverse purposes, leading to multifaceted travel behaviors. Understanding travel movement patterns is crucial in developing sustainable planning for urban tourism. Built on network science, this article discusses 12 key topologies of travel patterns/flow occurring in a city network by applying network motif analytics. The 12 significant types of travel mobility can account for approximately 50% of the total movement patterns. In addition, this study presents variations in travel movement patterns depending on not only different lengths of stay in topological structures of travel mobility, but also relative proportions of each type. As a result, this article suggests an interdisciplinary approach that adopts the network science method to better understand city travel behaviors. Important methodological and practical implications that could be useful for city destination planners are suggested.

Original languageEnglish
JournalJournal of Travel Research
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • length of stay
  • mobile big data analytics
  • network motif
  • travel mobility
  • urban tourism

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Tourism, Leisure and Hospitality Management

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