A technical analysis approach to tourism demand forecasting

被引:15
|
作者
Petropoulos, C
Nikolopoulos, K [1 ]
Patelis, A
Assimakopoulos, V
机构
[1] Univ Lancaster, Sch Management, Dept Management Sci, Lancaster Ctr Forecasting, Lancaster LA1 4YX, England
[2] Natl Tech Univ Athens, Sch Elect & Comp Engn, Forecasting Syst Unit, Zografou Athens 15773, Greece
[3] Minist Ecol & Finance, Informat Soc, Athens 10180, Greece
关键词
D O I
10.1080/13504850500065745
中图分类号
F [经济];
学科分类号
02 ;
摘要
Tourism demand forecasts are of great economic value both for the public and private sector. Any information concerning the future evolution of tourism flows, is of great importance to hoteliers, tour operators and other industries concerned with tourism or transportation, in order to adjust their policy and corporate finance. In the last few decades, numerous researchers have studied international tourism demand and a wide range of the available forecasting techniques have been tested. Major focus has been given to econometric studies that involve the use of least squares regression to estimate the quantitative relationship between tourism demand and its determinants. However, econometric models usually fail to outperform simple time series extrapolative models. This article introduces a new approach to tourism demand forecasting via incorporating technical analysis techniques. The proposed model is evaluated versus a range of classic univariate time series methods in terms of forecasting and directional accuracy.
引用
收藏
页码:327 / 333
页数:7
相关论文
共 50 条
  • [41] Forecasting Tourism Demand With a New Time-Varying Forecast Averaging Approach
    Sun, Yuying
    Zhang, Jian
    Li, Xin
    Wang, Shouyang
    [J]. JOURNAL OF TRAVEL RESEARCH, 2023, 62 (02) : 305 - 323
  • [42] A meta-analysis of international tourism demand forecasting and implications for practice
    Peng, Bo
    Song, Haiyan
    Crouch, Geoffrey I.
    [J]. TOURISM MANAGEMENT, 2014, 45 : 181 - 193
  • [43] A Study on the Tourism Combining Demand Forecasting Models for the Tourism in Korea
    Son, H. G.
    Ha, M. H.
    Kim, S.
    [J]. KOREAN JOURNAL OF APPLIED STATISTICS, 2012, 25 (02) : 251 - 259
  • [44] Tourism demand modelling and forecasting: how should demand be measured?
    Song, Haiyan
    Li, Gang
    Witt, Stephen F.
    Fei, Baogang
    [J]. TOURISM ECONOMICS, 2010, 16 (01) : 63 - 81
  • [45] Forecasting daily tourism demand with multiple factors
    Xu, Shilin
    Liu, Yang
    Jin, Chun
    [J]. ANNALS OF TOURISM RESEARCH, 2023, 103
  • [46] Tourism demand forecasting - a review on the variables and models
    Khaidi, Sarah Mohd
    Abu, Noratikah
    Muhammad, Noryanti
    [J]. 2ND INTERNATIONAL CONFERENCE ON APPLIED & INDUSTRIAL MATHEMATICS AND STATISTICS, 2019, 1366
  • [47] Forecasting tourism demand using consumer expectations
    Claveria, Oscar
    Datzira, Jordi
    [J]. TOURISM REVIEW, 2010, 65 (01) : 18 - 36
  • [48] Forecasting tourism demand with helpful online reviews
    Liao, Zhixue
    Gou, Xinyu
    Wei, Qiang
    Xing, Zhibin
    [J]. NANKAI BUSINESS REVIEW INTERNATIONAL, 2024,
  • [49] Forecasting Oil Demand with the Development of Comprehensive Tourism
    Huang, Yanrong
    Li, Shuaihao
    Wang, Rui
    Zhao, Zhijiang
    Huang, Bin
    Wei, Bo
    Zhu, Guangming
    [J]. CHEMISTRY AND TECHNOLOGY OF FUELS AND OILS, 2021, 57 (02) : 299 - 310
  • [50] Group pooling for deep tourism demand forecasting
    Zhang, Yishuo
    Li, Gang
    Muskat, Birgit
    Law, Rob
    Yang, Yating
    [J]. ANNALS OF TOURISM RESEARCH, 2020, 82