基于网络信息搜索的旅游需求预测——来自黄金周的证据  

Forecasting of Tourism Demand in the Golden Week with Online Information Search

作　　者：王炼[1] 贾建民[1,2] 

机构地区：[1]西南交通大学经济管理学院,成都610031 [2]香港中文大学工商管理学院

出　　处：《系统管理学报》2014年第3期345-350,358,共7页Journal of Systems & Management

基　　金：国家自然科学基金资助项目(71090402);西南交通大学博士研究生创新基金资助项目;中央高校基本科研业务费专项资金资助项目

摘　　要：基于旅游需求预测和信息搜索理论,结合黄金周期间景区的旅游数据和网络搜索数据,探讨了网络信息搜索在旅游需求预测中的潜在作用。实证研究结果显示,网络信息搜索与旅游需求之间存在显著的正相关关系。相对于自回归基准模型,基于网络信息搜索的模型能够显著提高旅游需求预测的准确性,在MAE和RMSE这2个指标上样本外预测精度分别提高约41%和43%。Following previous studies on tourism demand and information search, this paper empirically investigates the potential role of online information search in tourism demand forecasting. It combines data on tourist arrivals and search queries of well-known scenic spots during the Golden Week in China. Empirical results show that online information search has significant positive impact on tourism demand forecasting. In addition, the forecasting model with information search improves the forecasting accuracy significantly. Compared with the baseline autoregressive model, the proposed model can enhance the out- of-sample forecast accuracy by about 41% and 43% on average, in terms of measures of MAE and RMSE, respectively.

关 键 词：旅游需求 预测模型 信息搜索 

分 类 号：F272.1[经济管理—企业管理]