Hot topics and emerging trends in tourism forecasting research: A scientometric review

Han Liu, Ying Liu, Yonglian Wang, Changchun Pan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

68 Citations (Scopus)

Abstract

Tourism forecasting has been a focal point of tourism research over the past few decades as a result of the corresponding rapid development and expansion of the tourism industry. A bibliometric analysis, based on 543 articles retrieved from the Web of Science Core Collection database, was carried out to provide insights into hot topics as well as emerging trends in tourism forecasting research. The results show that the research outputs related to tourism forecasting have grown rapidly since 2006. The observed hot topics in tourism forecasting were to predict tourism demand via various models, including time series models, econometric models, and artificial intelligence-based methods, and to compare the forecasting accuracy of models. An emerging trend of tourism forecasting is to use methods based on data from a web-based search engine. Our study provides insights and valuable information for researchers to identify new perspectives on hot topics and research frontiers.

Original languageEnglish
Pages (from-to)448-468
Number of pages21
JournalTourism Economics
Volume25
Issue number3
Early online date4 Nov 2018
DOIs
Publication statusPublished - 1 May 2019
Externally publishedYes

Keywords

  • bibliometric analysis
  • CiteSpace
  • knowledge mapping
  • research frontiers
  • scientometrics
  • tourism forecasting

ASJC Scopus subject areas

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

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