Demand forecasting and information platform in tourism

被引:12
|
作者
Li, Yue [1 ]
Jiang, Qi-Jie [2 ]
机构
[1] Sichuan Agr Univ, Tourism Sh, Chengdu, Peoples R China
[2] Sichuan Univ, Business Sch, Chengdu, Peoples R China
来源
OPEN PHYSICS | 2017年 / 15卷 / 01期
关键词
Tourism supply chain; Information platform; Demand forecasting ability; Information processing ability; Information acquiring ability; ARTIFICIAL NEURAL-NETWORKS; SUPPLY CHAIN; POLICY;
D O I
10.1515/phys-2017-0027
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Information asymmetry and the bullwhip effect have been serious problems in the tourism supply chain. Based on platform theory, this paper established a mathematical model to explore the inner mechanism of a platform's influence on stakeholders' ability to forecast demand in tourism. Results showed that the variance of stakeholders' demand predictions with a platform was smaller than the variance without a platform, which meant that a platform would improve predictions of demand for stakeholders. The higher information-processing ability of the platform also had other effects on demand forecasting. Research on the inner logic of the platform's influence on stakeholders has important theoretical and realistic value. This area is worthy of further study.
引用
收藏
页码:247 / 252
页数:6
相关论文
共 50 条
  • [41] Deep Learning Framework for Forecasting Tourism Demand
    Laaroussi, Houria
    Guerouate, Fatima
    Sbihi, Mohamed
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON TECHNOLOGY MANAGEMENT, OPERATIONS AND DECISIONS (ICTMOD), 2020,
  • [42] Hierarchical pattern recognition for tourism demand forecasting
    Hu, Mingming
    Qiu, Richard T. R.
    Wu, Doris Chenguang
    Song, Haiyan
    [J]. TOURISM MANAGEMENT, 2021, 84
  • [43] Data source combination for tourism demand forecasting
    Hu, Mingming
    Song, Haiyan
    [J]. TOURISM ECONOMICS, 2020, 26 (07) : 1248 - 1265
  • [44] Forecasting tourism demand: a cubic polynomial approach
    Chu, FL
    [J]. TOURISM MANAGEMENT, 2004, 25 (02) : 209 - 218
  • [45] Tourism demand with subtle seasonality: Recognition and forecasting
    Wang, Haiyan
    Hu, Tao
    Wu, Huihui
    [J]. TOURISM ECONOMICS, 2023, 29 (07) : 1865 - 1889
  • [46] Knowledge mapping of tourism demand forecasting research
    Zhang, Chengyuan
    Wang, Shouyang
    Sun, Shaolong
    Wei, Yunjie
    [J]. TOURISM MANAGEMENT PERSPECTIVES, 2020, 35
  • [47] Tourism demand forecasting: A deep learning approach
    Law, Rob
    Li, Gang
    Fong, Davis Ka Chio
    Han, Xin
    [J]. ANNALS OF TOURISM RESEARCH, 2019, 75 : 410 - 423
  • [48] TOURISM DEMAND FORECASTING USING ARIMA MODEL
    Karadzic, Vesna
    Pejovic, Bojan
    [J]. TRANSFORMATIONS IN BUSINESS & ECONOMICS, 2020, 19 (2B): : 731 - 745
  • [49] Forecasting Tourism Demand with Decomposed Search Cycles
    Li, Xin
    Law, Rob
    [J]. JOURNAL OF TRAVEL RESEARCH, 2020, 59 (01) : 52 - 68
  • [50] CRUISE TOURISM DEMAND FORECASTING - THE CASE OF DUBROVNIK
    Pavlic, Ivana
    [J]. TOURISM AND HOSPITALITY MANAGEMENT-CROATIA, 2013, 19 (01): : 125 - 142