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Modeling and forecasting tourism demand: the case of flows from Mainland China to Taiwan

Author

Listed:
  • Luiz Moutinho

    ()

  • K.-H. Huarng

    ()

  • Tiffany Yu

    ()

  • C.-Y. Chen

    ()

Abstract

The study of tourism demand is attracting more and more attention. Hence, it is important to understand the variables that affect tourism demand and to forecast the demand. Many studies have been conducted to analyze the demands in various countries. Recently, China has been expected to become one of the largest originators of outbound tourists in the world. Hence, it is interesting to explore what the variables are that affect the Mainland Chinese arrivals to Taiwan and to forecast its corresponding tourism demand. This study applies neural networks to select proper models, and then to forecast the demand. Copyright Springer-Verlag 2008

Suggested Citation

  • Luiz Moutinho & K.-H. Huarng & Tiffany Yu & C.-Y. Chen, 2008. "Modeling and forecasting tourism demand: the case of flows from Mainland China to Taiwan," Service Business, Springer;Pan-Pacific Business Association, vol. 2(3), pages 219-232, September.
  • Handle: RePEc:spr:svcbiz:v:2:y:2008:i:3:p:219-232
    DOI: 10.1007/s11628-008-0037-3
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    File URL: http://hdl.handle.net/10.1007/s11628-008-0037-3
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    References listed on IDEAS

    as
    1. Maria De Mello & Alan Pack & M. Thea Sinclair, 2002. "A system of equations model of UK tourism demand in neighbouring countries," Applied Economics, Taylor & Francis Journals, vol. 34(4), pages 509-521.
    2. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141.
    3. V. Kerry Smith & Raymond J. Kopp, 1980. "The Spatial Limits of the Travel Cost Recreational Demand Model," Land Economics, University of Wisconsin Press, vol. 56(1), pages 64-72.
    4. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    5. Indro, D. C. & Jiang, C. X. & Patuwo, B. E. & Zhang, G. P., 1999. "Predicting mutual fund performance using artificial neural networks," Omega, Elsevier, vol. 27(3), pages 373-380, June.
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    Cited by:

    1. Keating, Byron W. & Kriz, Anton, 2008. "Outbound tourism from China: literature review and research agenda," MPRA Paper 40509, University Library of Munich, Germany.
    2. repec:eee:touman:v:50:y:2015:i:c:p:130-141 is not listed on IDEAS

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