The DOI matches its Crossref record; 180 of the 180 references it cites were found in a registry or an index.
A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting
Open accessAbstract
This study reviews 211 key papers published between 1968 and 2018, for a better understanding of how the methods of tourism demand forecasting have evolved over time. The key findings, drawn from comparisons of method-performance profiles over time, are that forecasting models have grown more diversified, that these models have been combined, and that the accuracy of forecasting has been improved. Given the complexity of determining tourism demand, there is no single method that performs well for all situations, and the evolution of forecasting methods is still ongoing.
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Citations
Cites
Time Series Analysis: Forecasting and Control
Geurts, M., Box, G. E. P., & Jenkins, G. M. (1977) · Journal of Marketing Research · doi:10.2307/3150485 · Cited by 19,186
Deaton, A. (1980) · Oxford University Research Archive (ORA) (University of Oxford) · Cited by 4,258
Forecasting with artificial neural networks:
Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229
Bates, J. M., & Granger, C. W. J. (1969) · Journal of the Operational Research Society · doi:10.1057/jors.1969.103 · Cited by 3,201
Predicting the Present with Google Trends
CHOI, H., & VARIAN, H. (2012) · Economic Record · doi:10.1111/j.1475-4932.2012.00809.x · Cited by 2,354
Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model
Pesaran, M. H., Schuermann, T., & Weiner, S. M. (2004) · Journal of Business & Economic Statistics · doi:10.1198/073500104000000019 · Cited by 1,456
Tourism demand modelling and forecasting—A review of recent research
Song, H., & Li, G. (2008) · Tourism Management · doi:10.1016/j.tourman.2007.07.016 · Cited by 1,415
Self-citationForecasting tourism demand: A review of empirical research
Witt, S. F., & Witt, C. A. (1995) · International Journal of Forecasting · doi:10.1016/0169-2070(95)00591-7 · Cited by 895
The role of transport infrastructure in international tourism development: A gravity model approach
Khadaroo, J., & Seetanah, B. (2008) · Tourism Management · doi:10.1016/j.tourman.2007.09.005 · Cited by 669
Miller, G. (2001) · Tourism Management · doi:10.1016/s0261-5177(00)00067-4 · Cited by 604
Metadata
- Authors
- Song, H., Qiu, R. T. R., & Park, J.
- Venue
- Annals of Tourism Research
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 75
- Pages
- 338-362
- ISSN
- 0160-7383 (ISSN-L)
- OpenAlex
- W2939264787
- Cited by
- 523
- References
- 180
- FWCI
- 41.14
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting. https://app.cochat.ai/papers/10.1016/j.annals.2018.12.001
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- Song, H., Qiu, R. T. R., & Park, J. (2019). A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting. Annals of Tourism Research. https://doi.org/10.1016/j.annals.2018.12.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
