Predicting Tourist Demand Using Big Data

Haiyan Song, Han Liu

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

73 Citations (Scopus)

Abstract

Big data is one of the most important new tools that have impacted the world travel industry. It also plays an important role in determining the ways in which tourism businesses and non-governmental organizations formulate their strategies and policies. However, very limited academic research has been conducted into tourism forecasting using big data due to the difficulties in capturing, collecting, handling, and modeling this type of data, which is normally characterized by its privacy and potential commercial value. In this chapter, we define big data in the context of tourism forecasting and summarize the changes it has brought about in tourism business decision-making. A framework of tourism forecasting using big data is then presented.

Original languageEnglish
Title of host publicationTourism on the Verge
EditorsUlrike Gretzel
PublisherSpringer Nature
Pages13-29
Number of pages17
DOIs
Publication statusPublished - 2017

Publication series

NameTourism on the Verge
VolumePart F1056
ISSN (Print)2366-2611
ISSN (Electronic)2366-262X

Keywords

  • Big data
  • Forecasting
  • Mixed frequency
  • Tourist demand

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management
  • Social Sciences (miscellaneous)
  • Education
  • Geography, Planning and Development

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