Volatility, exponential smoothing, regression and Naïve 2 models are considered singly and in combination
in terms of forecasting demand for international tourism. These models generate accurate
predictions of tourism flows, but their prime utility is when combined with other models. Usually,
models are combined by means of purely statistical criteria. We show that goal programming (GP) offers
an alternative, flexible approach to model combination. GP offers planners a practical solution to tourism
forecasting problems, since the method is more adaptable than conventional minimisation of prediction
error, by permitting practitioners to prioritise a series of management related goals. Forecasters can focus
on longer- and short-term goals, minimising forecast under- and over-estimation and/or concentrate on
prediction errors in tourism flows at various times of the year.