基于预警平台大数据的事件旅游客流时空分布研究  

The Study on the Temporal and Spatial Distribution of Event Tourism Based on Large-scale Tourism Early Warning Platform

作　　者：王玲[1] 代前进 吴晓隽[1] Wang Ling;Dai Qianjin;Wu Xiaojun(The Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China)

机构地区：[1]东华大学旭日工商管理学院,上海200051

出　　处：《数据分析与知识发现》2018年第8期31-40,共10页Data Analysis and Knowledge Discovery

基　　金：国家自然科学基金项目"分享经济的空间行为及其社会经济影响研究"(项目编号:71774029)的研究成果之一

摘　　要：【目的】对城市节庆期间各景区客流进行可视化,分析事件旅游客流时空分布规律及影响因素。【方法】在客流大数据的支撑下,以上海旅游节作为研究样本,运用GIS对上海80家A级景区客流数据进行空间信息表达,并构建理论模型检验影响因素。【结果】萌生性旅游资源突破事件旅游客流实现旅游需求的时间、空间障碍;原生性旅游资源是引发旅游者客流集聚的动机所在,导致客流快速汇集。事件旅游客流空间集聚特征明显,整体上由客流集聚中心区域向四周递减,并呈多核模式的空间分布规律;事件旅游客流时间分布改变"倒U型",时空阻隔导致热点景区集聚效应更强。旅游资源禀赋、交通区域条件、事件旅游产品竞争力、事件旅游服务接待能力对事件旅游客流集聚具有促进作用,事件旅游配套设施不再是吸引事件旅游客流的关键要素,景区承载力大并不能拉动旅游客流的集聚。【局限】未对客流的动态路径进行深入探讨。【结论】GIS技术与大数据结合,可直观表达客流分布规律。[Objective] This paper visualizes the big data of festival visitors, aiming to analyze their movement patterns and influencing factors. [Methods] We used the GIS tools to analyze the tourist flow data of 80 scenic spots during Shanghai Tourism Festival, and constructed metrological model to examine the influencing factors. [Results] We found that initiation tourism resources, which broke the obstacles facing event tourists, included the motivation of tourists gathering and rapid flows. The number of tourists declined fi＇om the multiple event centers to surrounding areas. The time distribution of tourist flow did not follow the classic ＂inverted U-shape＂, and then led to more agglomeration effects. Tourism resource endowment, traffic conditions, competitiveness of tourism products, and tourism reception could all promote tourists gathering, while facilities （i.e. capacity） was no longer the key element in attracting visitors. [Limitations] More research is needed to discuss the dynamic path of tourist flow. [Conclusions] GIS and big data technology can be used to present the visitors＇ flow.

关 键 词：事件旅游 客流 时空分布 集聚效应 影响因素 

分 类 号：F592.7[经济管理—旅游管理]