Tourism Demand Forecasting - Delphi Method
Methodology  -  Lake State Examples - Other Examples         
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Uysal, M. and J. L. Crompton. 1985. "An Overview of Approaches Used to Forecast Tourism Demand." Journal of Travel Research 23(Spring):7-15.

This paper presents a brief review of the tourism forecasting literature as of 1985. Three qualitative techniques are examined: simple survey techniques, Delphi models and judegement-aided models. Three quantitative techniques are also reviewed: Time-series, gravity and trip generation models and multivariate regression models.

Archer, B. H. 1980. "Forecasting Demand, Quantitative and Intuitive Techniques." International Journal of Tourism Management 1(1):5-12.

This paper reviews the art of demand forecasting in tourism as of 1980. Time-series analysis, the causal methods of multivariate regression and gravity and trip generation models, and the qualitative techniques of surveys, expert group processes and Delphi modeling are all discussed. The author concludes that integrated techniques, which combine quantitative methods with expert judgment may be the most accurate.

Archer, B. H. 1976. Demand Forecasting in Tourism. Bangor, University of Wales Press.

This book explores the sate of the art of tourism forecasting in 1976. In particular the techniques of multi-variable regression models, gravity and trip generation models, linear system analysis and expert-based Delphi models are explained. The components and theory of tourism demand are detailed and the theoretical basis of each model is outlined.

Lake States Examples:

Other Examples:

Tideswell, C., T. Mules and B. Faulkner. 2001. "An Integrative Approach to Tourism Forecasting: A Glance in the Rearview Mirror." Journal of Travel Research 40(November 2001):162-171.

  • This study evaluated the results of tourism forecasting exercise in South Australia for the period of 1996-1998. An integrated times-series and Delphi process was used to forecast tourism demand from both the international and domestic market. Three methods of generating time-series forecasts were used: Holt's exponential smoothing; a "naive" method using average annual rate of change from the past 11 years; and a linear trend using regression analysis. A group of 26 tourism industry practitioners responded to a Delphi survey and provided comments in a follow-up group meeting process. The final forecasting method used was based on the results of the Delphi process. Grouped forecasting trends (e.g. all international visitors) were quite accurate, but forecasts for segments of the market (e.g. Japanese visitors) were not as accurate. This was particularly true for small market segments. Over all, the "naive" approach to demand forecasting was most accurate, confirming the results of earlier studies.
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