Accurate predictions of future business activities are important for business decisions. As a consequence, powerful but simple forecasting processes are urgently sought after by decision-makers. This study presents a tourism demand forecasting system for Hong Kong based on the web techniques to help relevant stakeholders within the tourism industry to make better decisions. The system generates the forecasts of tourism arrivals, tourism expenditure, demand for hotel rooms, sectoral demands and outbound tourist flows. The autoregressive distributed lag (ADL) Model is employed by this web-based forecasting system. The ADL model relates a set of influencing factors to the demand for tourism in Hong Kong, and generates both statistical as well as scenario forecasts of tourism demand in Hong Kong. In addition, the system also allows experts’ adjustments to be made to the statistical forecasts.
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