An Introduction to Tourism Demand Forecasting           
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Frechtling, D. C. 1996. Practical Tourism Forecasting. Oxford, Butterworth Heinemann.

This book provides a comprehensive review of the tourism demand forecasting literature. The book is intended to provide a foundation for understanding the various methods of tourism demand forecasting available and to encourage the reader to try his or her hand at forecasting some aspect of tourism demand. The book covers both quantitative and qualitative techniques of tourism demand forecasting.

Crouch, G. 1995. "A Meta-Analysis Study of International Tourism Demand." Annals of Tourism Research 22(1):103-118.

This study uses meta-analysis to integrate the empirical findings of 80 studies of international tourism demand. The reported results support the assumption that demand elasticities for international tourism vary regionally in terms of both origin and destination. The demand coefficients are situation-specific and, therefore, aggregation of demand coefficients across country pairs is not possible. While there will always be the need to estimate demand coefficients from original data, the author argues it would be counterproductive to ignore the lessons and results from the past when so much already exists. The past results can indeed be used to guide the estimation of demand coefficients in future studies by using constrained or Bayesian regression approaches.

Faulkner, B. and P. Valerio. 1995. "An integrative approach to tourism demand forecasting." Tourism Management 16(1):29-37.

This paper situates tourism forecasting within the context of the tourism management activities it is supposed to serve. Too often, tourism forecasting and the building of econometric models have become an end in itself. Instead, techniques that rely on both quantitative analysis and expert involvement are touted as more useful as they integrate forecasting into the strategic planning exercise. This allows decision makers to understand the forecasting process and may lead to decision-making which more reflective of the tourism forecasts. Likewise, while citing chaos theory the authors suggest that expert opinion can make very valuable contributions to the forecasting exercise. The process that the Australian Tourist Commission goes through to set tourism targets, which are essentially forecasts, is cited as an example of a valuable integrated approach.

Smith, S. L. J. 1995. Forecasting Tourism Demand and Market Trends. In Tourism Analysis: A Handbook. Essex, Longman Group Limited. Second Edition: 116-149.

This chapter introduces the concepts of tourism demand and forecasting. Almost all forecasting involves predicting the tourism demand at some point in the future. In the neoclassical conception of demand, demand is seen as a function of price. However many other variable, or demand shifters, may have an influence on price. From the tourism perspective these include age, education, tastes, previous experience with the product, advertising, product innovation, government policy or new technology. As a luxury good, the demand for tourism tends to be quite elastic while the income elasticity of different tourism products can differ considerably, as some recreation goods may actually show declining consumption with increasing income. The chapter reviews the forecasting methods of simple regression, gravity models, probabilistic travel model, and the Delphi technique.

Archer, B. H. 1994. Demand Forecasting and Estimation. Travel, Tourism, and Hospitality Research: A Handbook for Managers and Researchers. J. R. Brent Ritchie and Charles R. Goeldner (ed.), New York, John Wiley and Sons Ltd. Second Edition: 105-114.

Demand forecasting in tourism research is reviewed from the perspective of which method is most appropriate given the research question, the time period specified and the information needs of managers. Factors which will govern the choice of method include the purpose, the time period being forecasted, the degree of accuracy required, the availability of information, the forecasting environment and the cost of producing the forecast. Inaccuracies in forecasting result may result from five different factors: inappropriate model, incorrect use, error calculation in relationships in model, significant variables omitted, and data used may have been inadequate or inappropriate. A review of quantitative, qualitative and technological forecasting techniques and the factors which influence tourism demand are also included.

Witt, S. F. and C. A. Martin. 1989. Demand Forecasting in Tourism and Recreation. Progress in Tourism, Recreation and Hospitality Management: Volume 1. C.P. Cooper (ed.), New York, Belhaven Press: 4-32.

This book chapter provides a detailed description of the many tourism demand forecasting methodologies available to researchers including: univariate time-series; multivariate regression (econometric); Box-Jenkins multivariate method; and qualitative forecasting techniques. They also provide a survey of literature on accuracy analysis in tourism demand forecasting.

Calantone, R. J., C. A. di Benedetto and D. Bojanic. 1987. "A Comprehensive Review of the Tourism Forecasting Literature." Journal of Travel Research 26(2):28-39.

This paper reviews the state of tourism demand forecasting, describes the different methods used and critiques each method in turn. They provide a useful table with ranks the different forecasting methods based on their most appropriate time horizon, cost of implementation and complexity of the approach. The paper concludes that are many deficiencies in tourism demand modeling not only with the way the methods are applied, but also how they are reported in the literature. The authors suggest tourism demand forecasting needs to be evaluated non only against other methods, but also against the most common practice of forecasting - expert "guessing". More time needs to be put into model validation, especially in the case of explanatory approaches, and complex model building should not be undertaken for its own sake as there needs to be a good explanation of its benefits over simpler approaches.

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 judgment-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.

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