空间关联视角下北京市不同星级酒店分布规律及影响因素研究
Research on Distribution Patterns and Influencing Factors of Hotels of Different Star Ratings in Beijing City from a Spatial Association Perspective
李美仪 1李玲 2麦雄发1
作者信息
- 1. 南宁师范大学 数学与统计学院,南宁 530001
- 2. 南宁师范大学 北部湾环境演变与资源利用教育部重点实验室,南宁 530001
- 折叠
摘要
利用地理加权协同定位商模型,从空间关联角度研究北京市不同星级酒店空间分布模式及交通和旅游景点各类设施对其影响,揭示双方关联的强度和方向,为未来商业地理相关研究及酒店的空间格局优化调整提供重要的参考依据.结果表明:(1)1 km范围内,三星级和二星级及以下酒店显著聚集,四星级酒店最易聚集在其他星级酒店周边,五星级酒店附近最易吸引三、四星级酒店.(2)不同星级酒店受交通影响的程度强于旅游景点.地铁站、汽车站对星级酒店的影响由强到弱,而城市广场、国家级景点等旅游景点的影响由强到弱.地铁站对各星级酒店的局部空间关联性呈现"中心强、外围弱"的特征,城市广场对各星级酒店的局部特征呈"中心集聚、四周辐射"的分布趋势.
Abstract
This study utilized the geographically weighted colocation quotient model to explore the spatial distri-bution patterns of different star-rated hotels in Beijing and the impact of transportation and various tourist attractions on them from a spatial association perspective.The strength and direction of these associations were revealed,provi-ding important reference points for future commercial geography research and the spatial pattern optimization of ho-tels.The results indicate that:(1)Within a 1 km radius,three-star and two-star hotels are significantly clustered,with four-star hotels most likely clustered around other star-rated hotels,and five-star hotels most likely attracting three-star and four-star hotels nearby.(2)Different star-rated hotels are more influenced by transportation than tour-ist attractions.Among them,the impact of subway stations and bus stations on star-rated hotels varies from strong to weak,while the impact of urban squares,national-level scenic spots,and other tourist attractions varies similarly.Subway stations exhibit a"strong center,weak periphery"spatial association characteristic with star-rated hotels,while urban squares show a trend of"central aggregation and radiating distribution"around various star-rated hotels.
关键词
空间关联/地理加权协同区位商/星级酒店/北京市Key words
spatial association/geographically weighted colocation quotient/star-rated hotels/Beijing City引用本文复制引用
基金项目
国家自然科学基金(41801168)
广西壮族自治区千骨计划(第五期)()
出版年
2024
NETL
NSTL
万方数据