A meta-analysis of international tourism demand forecasting and implications for practice

Bo Peng, Haiyan Song, Geoffrey I. Crouch

Research output: Journal article publicationJournal articleAcademic researchpeer-review

177 Citations (Scopus)


Numerous studies on tourism forecasting have now been published over the past five decades. However, no consensus has been reached in terms of which types of forecasting models tend to be more accurate and in which circumstances. This study uses meta-analysis to examine the relationships between the accuracy of different forecasting models, and the data characteristics and study features. By reviewing 65 studies published during the period 1980-2011, the meta-regression analysis shows that the origins of tourists, destination, time period, modeling method, data frequency, number of variables and their measures and sample size all significantly influence the accuracy of forecasting models. This study is the first attempt to pair forecasting models with the data characteristics and the tourism forecasting context. The results provide suggestions for the choice of appropriate forecasting methods in different forecasting settings.
Original languageEnglish
Pages (from-to)181-193
Number of pages13
JournalTourism Management
Publication statusPublished - 1 Jan 2014


  • Forecasting accuracy
  • International tourism demand
  • Meta-analysis

ASJC Scopus subject areas

  • Development
  • Transportation
  • Tourism, Leisure and Hospitality Management
  • Strategy and Management


Dive into the research topics of 'A meta-analysis of international tourism demand forecasting and implications for practice'. Together they form a unique fingerprint.

Cite this