基于百度指数的天山天池景区客流量预测研究  

Research on Passenger Flow Prediction of Tianshan Tianchi Scenic Spot Based on Baidu Index

作　　者：康梓蝶 李啸虎[1] KANG Zidie;LI Xiaohu(College of Tourism,Xinjiang University of Finance and Economics,Urumqi 830012,China)

机构地区：[1]新疆财经大学旅游学院,乌鲁木齐830012

出　　处：《职业技术》2024年第2期99-108,共10页Vocational Technology

基　　金：新疆维吾尔自治区社会科学基金项目“新疆旅游业发展高质量水平评价、障碍诊断与潜力研究”(19BYJ038);新疆财经大学研究生科研创新项目“新疆文旅产业融合水平的多维测度及路径提升”(XJUFE2023K052)。

摘　　要：对游客数量进行预测有助于景区的可持续发展,也为景区的合理安排和规划提供依据。利用2021年新疆天山天池景区日游客量的数据,通过协整检验和格兰杰因果检验,借助ARMA模型和自回归分布滞后模型对客流量进行预测,最终将预测结果与实际游客量进行对比。结果表明:(1)新疆天山天池实际游客量与百度指数搜索的关键词存在长期均衡关系;(2)新疆天山天池实际游客量与百度指数搜索的关键词均存在双向的格兰杰因果关系;(3)加入百度关键词后,模型的拟合优度更高,预测效果更好;(4)预测精度越高,越能够有效判断用户对景区的关注度,通过对网络数据的搜集整理,可以为有关部门提供决策依据。Predicting the number of tourists is helpful for the sustainable development of scenic spots and also provides a basis for the reasonable arrangement and planning of scenic spots.Using the daily tourist volume data of Tianshan Tianchi Scenic Spot in Xinjiang in 2021,through cointegration test and Granger causality test,the ARMA model and autoregressive distribution lag model were used to predict the passenger flow.Finally,the predicted results were compared with the actual tourist volume to determine the accuracy of the prediction.The results indicate that:(1)there is a long-term equilibrium relationship between the actual tourist volume of Tianshan Tianchi Scenic Spot in Xinjiang and the keywords searched by Baidu Index;(2)there is a bidirectional Granger causality relationship between the actual tourist volume of Tianshan Tianchi Scenic Spot in Xinjiang and the keywords searched by Baidu Index;(3)after adding Baidu keywords,the goodness of fit of the model is higher and the prediction effect is better;(4)the higher the prediction accuracy,the more effective it is to determine the user’s attention to the scenic spot.Therefore,by collecting and organizing network data,it can provide decision-making basis for relevant departments.

关 键 词：百度指数 景区客流量 格兰杰因果检验 ARMA模型 自回归分布滞后模型 

分 类 号：G482[文化科学—教育学]