Improving multi-step ahead tourism demand forecasting: A strategy-driven approach

Previous researches have proposed five strategies to deal with complex multi-step ahead forecasting tasks. However, these strategies have not received much attention in the field of tourism research and the performance of them is still unknown. Accordingly, we summarize the strategies used in multi-step ahead tourism demand forecasting articles and produce a comparative analysis of five strategies. By employing nine tourist arrival time series in Hong Kong, the study explores the performance of different strategy-driven forecasting approaches in tourism demand. The empirical results show that Direct and DIRMO (s = 2) strategies perform better than other strategies in terms of forecasting accuracy, but there is no significant difference between them, excepting the latter is lower than the former in computational complexity.