首页|基于排序选择模型的游客拥挤感知分析

基于排序选择模型的游客拥挤感知分析

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
  • 维普
基于游客拥挤感知机理和影响因素分析,采用意愿调查法对游客旅游线路特性、拥挤感知度和不同拥挤状态下的游客时空分布意向进行调查,定量分析不同旅游阶段信息、客流密度等因素对游客拥挤感知度的影响,基于排序选择模型,建立游客拥挤感知模型,并进行局部效应分析.结果表明:出行前(查询旅线信息方式等)、景区游览阶段(拥挤信息发布内容、景点停留时间等)的旅游信息变量对游客的拥挤感知度具有显著影响;景点停留时间每增加1 min,游客拥挤感知度为2、3、4的概率分别增加0.3%、增加1.1%、减少1.3%,研究可为旅游信息合理发布和游客合理分流提供基础数据.
Tourists' Congestion Perception Analysis Based on Ordered Choice Model
Based on the analysis of tourist congestion perception mechanism and influencing factors, stated preference convey is carried out to obtain tour route characteristic, congestion perception and tourists' temporal and spatial distribution intention under different congestion condition. The effect of influent factors such as tourism information obtained from different tourism stages and tourist density to tourist congestion perception is qualitatively analyzed. Based on the ordered choice model, tourists'congestion perception model is established and the partial effects are analyzed. The results show that factors which is before-tour and on tour such as information query mode of tourist route, dissemination content of congestion information and duration time have significant influences on tourists'congestion perception. The probability of the tourists'congestion perception degree (D=2, 3) will add 0.3% and 1.1% when the value of duration time adds 1 min, while the probability of the tourists'congestion perception degree (D=4) will reduce 1.3%.The analysis can provide basic data support for reasonable tourism information dissemination and tourists' temporal and spatial distribution.

traffic engineeringcongestion perception modelordered choice modeltourists'congestion perceptionpartial effects analysis

韩艳、武鑫森、杨光

展开 >

北京工业大学 交通工程北京市重点实验室,北京100124

交通工程 拥挤感知模型 排序选择模型 游客拥挤感知 局部效应分析

国家自然科学基金/National Natural Science Foundation of China北京市教委科技面上项目/Project of Science and Technology Plan of Beijing Municipal Education Commission

51308015KM201510005023

2017

10.16097/j.cnki.1009-6744.2017.04.021

交通运输系统工程与信息
中国系统工程学会

交通运输系统工程与信息

CSTPCDCSCD北大核心EI
影响因子：0.664
ISSN：1009-6744
年,卷(期)：2017.17(4)
  • 5
  • 3