文献类型：期刊文献

英文题名：The Baidu Index: Uses in predicting tourism flows -A case study of the Forbidden City

作者：Huang, Xiankai[1];Zhang, Lifeng[1];Ding, Yusi[1]

第一作者：Huang, Xiankai

通讯作者：Zhang, LF[1]

机构：[1]Beijing Union Univ, Tourism Coll, Beijing 100101, Peoples R China

第一机构：北京联合大学旅游学院

通讯机构：[1]corresponding author), Beijing Union Univ, Tourism Coll, Beijing 100101, Peoples R China.|[1141732]北京联合大学旅游学院;[11417]北京联合大学;

年份：2017

卷号：58

起止页码：301-306

外文期刊名：TOURISM MANAGEMENT

收录：;Scopus(收录号：2-s2.0-84962124364);WOS:【SSCI(收录号:WOS:000390642800031)】；

语种：英文

外文关键词：Baidu Index; Tourist attractions; Co-integration; Autoregressive moving average model; Autoregressive distributed lag model

摘要：Tourist overcrowding of sites during the 'Golden Week' is a not an uncommon situation in China today. Consequently the prediction of tourist numbers is important for tourist attractions management and planning. Most existing methods rely on well-structured statistical data published by the government. However, this approach is limited in two aspects: 1) there may be significant delays in the publication of such data and 2) the sample size can be small, leading to inaccurate predictions. This paper proposes a novel approach for predicting tourist flows based on the Baidu Index. The Index provides search history containing different keywords on a daily basis dating back to 2006. The approach uses co-integration theory and Granger causality analysis to find the relationship between the internet search data and the actual tourist flow. The paper compares analysis results obtained by two kinds of predictive models, with or without considering Baidu Index. The study shows that there is a long-term equilibrium relationship and Granger causal relation between the observed number of tourists and a set of related keywords in the Baidu Index. It indicated a positive correlation between the increasing Baidu keyword search index and the increasing observed tourist flow. (C) 2016 Published by Elsevier Ltd.