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Future Tourists' Characteristics and Decisions: The Use of Genetic Algorithms as a Forecasting Method

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  • Montserrat Hernández-López

    (Department of Institutional Economics, Economic Statistics and Econometrics, University of La Laguna, Facultad de Ciencias Económicas y Empresariales, Campus de Guajara, 38071 La Laguna, Tenerife, Islas Canarias, Spain)

Abstract

This paper applies genetic algorithms to tourism forecasting. To date, genetic algorithms have normally been used as an optimization method. Their application to forecasting with real-world data has not been studied extensively. The paper illustrates how genetic algorithms can be used for this purpose and the new kind of forecast that is obtained. Specifically, the algorithms are applied to a real tourist population, and the characteristics and decisions of each future tourist are forecast. The results suggest that tourism forecasting based on genetic algorithms could reduce the risk of decision making in tourism planning.

Suggested Citation

  • Montserrat Hernández-López, 2004. "Future Tourists' Characteristics and Decisions: The Use of Genetic Algorithms as a Forecasting Method," Tourism Economics, , vol. 10(3), pages 245-262, September.
    • Handle: RePEc:sae:toueco:v:10:y:2004:i:3:p:245-262
    DOI: 10.5367/0000000041895058
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    References listed on IDEAS

    as
    1. 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.
    2. Ann Clewer & Alan Pack & M. Thea Sinclair, 1990. "Forecasting Models For Tourism Demand In City Dominated And Coastal Areas," Papers in Regional Science, Wiley Blackwell, vol. 69(1), pages 31-42, January.
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