TY - JOUR
T1 - Forecasting turning points in tourism growth
AU - Wan, Shui Ki
AU - Song, Haiyan
N1 - Funding Information:
The second author would like to acknowledge the financial support of Natural Science Foundation of China (Grant No. NSFC71673233).
PY - 2018/9
Y1 - 2018/9
N2 - Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.
AB - Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.
KW - Combined probability forecast
KW - Hong Kong
KW - Quadratic probability score
KW - Tourism demand
UR - http://www.scopus.com/inward/record.url?scp=85050757399&partnerID=8YFLogxK
U2 - 10.1016/j.annals.2018.07.010
DO - 10.1016/j.annals.2018.07.010
M3 - Journal article
AN - SCOPUS:85050757399
SN - 0160-7383
VL - 72
SP - 156
EP - 167
JO - Annals of Tourism Research
JF - Annals of Tourism Research
ER -