Tourism demand modelling and forecasting: how should demand be measured?

被引:170
|
作者
Song, Haiyan [1 ]
Li, Gang [2 ]
Witt, Stephen F. [1 ]
Fei, Baogang [1 ]
机构
[1] Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, Hong Kong, Peoples R China
[2] Univ Surrey, Fac Management & Law, Guildford GU2 7XH, Surrey, England
关键词
tourist arrivals; tourist expenditure; forecasting accuracy; Hong Kong;
D O I
10.5367/000000010790872213
中图分类号
F [经济];
学科分类号
02 ;
摘要
Tourist arrivals and tourist expenditure, in both aggregate and per capita forms, are commonly used measures Of tourism demand in empirical research. This study compares these two measures In the context of econometric modelling and the forecasting Of tourism demand. The empirical Study focuses on demand for Hong Kong tourism by residents of Australia, the UK and the USA. Using the general-to-specific modelling approach, key determinants Of tourism demand are identified based on different demand measures. In addition, the forecasting accuracy of these demand Measures is examined. It is found that tourist arrivals in Hong Kong are influenced mainly by tourists' income and 'word-of-month'/habit persistence effects, while the tourism price in Hong Kong relative to that of the tourist origin country is the most important determinant Of tourist expenditure in Hong Kong. Moreover, the aggregate tourism demand models Outperform the per capita models, with aggregate expenditure models being the most accurate. The implications of these Findings for tourism decision making are that the choice of demand measure for forecasting models Should depend on whether the objective of the decision maker is to maximize tourist arrivals or expenditure (receipts), and also that the models should be specified in aggregate form.
引用
收藏
页码:63 / 81
页数:19
相关论文
共 50 条
  • [21] Forecasting tourism demand: the role of seasonality
    Vergori, Anna Serena
    [J]. TOURISM ECONOMICS, 2012, 18 (05) : 915 - 930
  • [22] Forecasting tourism demand: Methods and strategies
    Bar-On, RR
    [J]. ANNALS OF TOURISM RESEARCH, 2003, 30 (03) : 754 - 756
  • [23] A review of research on tourism demand forecasting
    Song, Haiyan
    Qiu, Richard T. R.
    Park, Jinah
    [J]. ANNALS OF TOURISM RESEARCH, 2019, 75 : 338 - 362
  • [24] A Hybrid Approach on Tourism Demand Forecasting
    Nor, M. E.
    Nurul, A. I. M.
    Rusiman, M. S.
    [J]. INTERNATIONAL SEMINAR ON MATHEMATICS AND PHYSICS IN SCIENCES AND TECHNOLOGY 2017 (ISMAP 2017), 2018, 995
  • [25] Forecasting tourism demand - An STM approach
    Greenidge, K
    [J]. ANNALS OF TOURISM RESEARCH, 2001, 28 (01) : 98 - 112
  • [26] Patterns of seasonality and tourism demand forecasting
    Vergori, Anna Serena
    [J]. TOURISM ECONOMICS, 2017, 23 (05) : 1011 - 1027
  • [27] Tourism demand forecasting with spatiotemporal features
    Li, Cheng
    Zheng, Weimin
    Ge, Peng
    [J]. ANNALS OF TOURISM RESEARCH, 2022, 94
  • [28] Forecasting International Tourism Demand in Thailand
    Chinnakum, Warattaya
    Boonyasana, Pimonpun
    [J]. THAI JOURNAL OF MATHEMATICS, 2016, : 231 - 244
  • [29] A review of tourism demand forecasting methodology
    Zheng, Yong
    Zeng, Zhonglu
    [J]. PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, 2010, : 213 - 218
  • [30] Effects of Multiple Financial News Shocks on Tourism Demand Volatility Modelling and Forecasting
    Zhang, Yuruixian
    Choo, Wei Chong
    Aziz, Yuhanis Abdul
    Yee, Choy Leong
    Wan, Cheong Kin
    Ho, Jen Sim
    [J]. JOURNAL OF RISK AND FINANCIAL MANAGEMENT, 2022, 15 (07)